1          Introduction

This paper is an extension of work originally presented in The 2016 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots [1].

For disabled people, using wheelchairs is an effective means for locomotion. However, since it is difficult for wheelchairs to negotiate steps, user movements are often restricted. Some reasons for the wheelchair’s difficulty include driving wheel slippage and/or vehicle imbalance. Numerous research programs aimed at improving wheelchair mobility on steps have been conducted, and the following potential solutions have been investigated: additional legs [2], multiple wheels and variable wheelbases [3], a combination of an adjustable center of gravity (COG) and multiple wheels [4], tracked vehicles [5], an additional driving wheel system [6], and changing the wheelchair posture to facilitate climbing [7]. In addition, Yoshikazu Mori studied a new step climbing and descending strategy using a manual wheelchair equipped with linear actuator mechanisms and a light portable ramp [8].

This study’s research group has previously investigated a cooperative step climbing method that can be used by a robot and a manual wheelchair connected via a passive link [9], and by using a teleoperated robot controlled by a caregiverthroughan intranet and a conventionalor electric drive wheelchair [10][11]. Our step climbing system, which is capable of reducing the burden imposed on the caregiver, takes advantage of the wheelchair user’s ability to judge external information (e.g., obstacles and distances between vehicles and steps), and the caregiver’s ability to teleoperate the system through an intranet.

To operate this step climbing system, both the wheelchair user and the caregiver will need sufficient training, particularly for the period when the wheelchair’s front wheels are close to the step, which is where the risk of a collision between the wheels and step is high. Furthermore, since this system uses autonomous control during the wheelchair step climbing process, it was necessary to implement a support system that can switch between teleoperation and autonomous control.

While the primary purpose of this paper is to describe our proposed support system for avoiding collisions between the wheelchair front wheels and step during stair ascents [1], we will also describe the concept behind our step climbing method, and provide a detailed theoretical analy-

Other reports of multiple vehicles cooperating to cross

Based on our preliminary measurements of the friction coefficients for the robot under wet and dry conditions on asphalt, concrete, wood, and interior flooring, the ground surface considered in this research was assumed to have a friction coefficient within the range of 0.6 to 0.9. The heights of steps located at the entrances of typical buildings and other structures were also measured, and a target step height of 120 mm, which accounts for more than 80% of the observed heights, was set.

This remainder of this paper is organized as follows: Section 2 describes the concept of cooperative step climbing, and Section 3 describes the robot and wheelchair used. Section 4 describes the step climbing process, and Section 5 provides a theoretical analysis of our proposed method. Section 6 describes an experiment using our proposed system and the results, and our conclusion is given in Section7.

2          Concept behind wheelchair care robot

As described above, since it is difficult for wheelchairs to climb steps, wheelchair user movements tend to be restricted. Most wheelchairs have two casters employed as front wheels and two driving rear wheels, and the center of gravity of a wheelchair with a seated user is high. Thus, when a wheelchair attempts to climb a step, high potentials for driving wheel slippage (Figure 1 (a)) and/or tipping over the vehicle (Figure 1 (b)) arise. In addition to step climbing situations, wheelchair users face difficulties at numerous other times. For example, it is difficult for a wheelchair user to open a door (Figure 2 (a)) or pick up an object that is on the floor or placed on a high shelf (Figure 2 (b)). Thus, under most current circumstances, most wheelchair users need a human assistant. However, taking care of a wheelchair and its user is hard work.

Figure 1: Reasons why wheelchairs are weak against steps: (a) driving wheel slippage, and (b) possibility of tipping over when the rear wheels transverse the step

Figure 2: Obstacles for wheelchair users other than step climbing: (a) door opening, and (b) picking up objects

The aim of this research is to create a teleoperated robot system that can be used by caregivers to provide assistance to vulnerable but esteemed persons (such as their elderly parents) from a distant location. In the next section, we will begin by evaluating a method for avoiding collisions between the front wheels of a wheelchair and a step wall.

3          Wheelchair and robot

The robot used in this research is “Tateyama”, which is a wheeled robot developed in this laboratory (Figure 3).

Figure 3: The wheelchair and robot

Table 1: Robot specifications

Overall length                1060 mm Overall height    985 mmTable 2: Wheelchair specifications

       Radius of front wheels (r_A)                           63 mm

       Radius of rear wheels (R_A)                          300 mm

       Wheelbase (l_A)                                              430 mm

       Hand rim position (l_LA)                                250 mm

Distance of center of gravity from

         the rear wheel axles (l_rA)                           149 mm

Height of mass above

the rear wheel axles (h_mA) 371 mm Height of push-handle (h_LA) 435 mm

       Mass (wheelchair + driver) (M_A)                92.7 kg

Figure 5: Robot manipulator

Figure 6: Rotary motion control of the robot shoulder using the robot body: (a) Front body of the robot, and (b) side view of stopper on the robot chest

The process begins with the wheelchair and robot deployed in a forward-and-aft configuration to traverse the step (Figure 4). When the wheelchair and the robot encounter a step, the robotic hands grasp the rotary shaft of the wheelchair push handle [14]. Table 1 and Table 2 list the specifications of the robot and wheelchair, respectively. The wheelchair and robot move at a constant speed (0.76 km/h). This robot is equipped with three pairs of wheels, and each pair consists of left and right wheels. The front pair are casters, whereas the middle and rear pairs are driving wheels. The front and rear pairs can be folded.

Figure 7: Human pushing an object

Figure 8: Sides of the robot: (a) in wheelchair climbing position, and (b) in robot climbing position

Figure 9: Stopper actions: (a) lifting the robot wheels, and (b) preventing the robot from falling down

The robot has manipulators attached to the left and right joints of its upper half. Since each arm has five degrees of freedom (5-DOF) and the hand has 1-DOF, the arm has a total of 6-DOF (Figure 5). In this paper, the length of the upper arm link (from Joint 2 (shoulder) to Joint 4 (elbow)) is l₂; the length of the forearm link (from Joint 4 to Joint 6) is l_4C. The manipulator joint angles are −90 deg ≤ φ₂ ≤ +90 deg and 0 ≤ φ₃ ≤ +100 deg. The right and left hands each have two fingers (Joint 6) in order to grasp and hold items (Figure 5).

The robot is equipped with a stopper mounted on the front part of its body (Figure 6 (a)), as described below, and is capable of limiting the passive rotational travel of the manipulators when it is pushing the wheelchair (Figure 6 (b)). This enables the robot to imitate the operation of a human pushing an object (Figure 7). The robot does not need to exert force around the shoulder axes because its upper arms push against the chest (i.e., the stopper) when pushing the wheelchair [11]. The motors mounted on the robot are connected to Faulhaber MCDC3003-S and MCDC3006S motion controllers (Faulhaber-Global, Schnaich, Germany). These are connected to a notebook personal computer (PC) mounted on the robot. The shape of the IntegralME wheelchair (NOVA, Carson, Ca) used in this study is typical among wheelchairs available on the market (Figure 3). The rear-wheel drive wheelchair is equipped with a TRD-1 electric drive unit (Acritech Co., Ltd.). Two motion controllers are added for the electric drive unit. The motion controllers on the wheelchair are connected to the notebook PC installed on the robot via a ZigBee wireless communications module. The wheelchairhas a push handle mechanism on its back (Figure 8 (a)) that is equipped with a rotary shaft in order to permit passive rotation of the handle. When the robot hands grasp this shaft, the two vehicles are connected. The stopper of the wheelchair is composed of front and rear bars. During the robot climbing process, the sides of the robot are opened, and the right and left manipulators are inserted into the stopper (Figure 8 (b)). The dual manipulators of the robot are equipped with touch sensors that allow them to detect contact with the stopper. The robot pushes the front bars by using the forearm links of the manipulators to lift its front wheels (Figure 9 (a)). The rear bars are used to prevent the robot from tipping over backward when its center of gravity shifts behind the contact point between the middle wheels and the ground (Figure 9 (b)).

The robot control mode can be switched between network-basedteleoperationand autonomouscontrol by the caregiver. In Figure 10, (a) is a system configuration diagram that shows the working device in the teleoperation mode, and Figure 10 (b) shows the system diagram of the autonomous control mode. These system configuration diagrams show only the working devices in each mode. When engaged in wheelchair step climbing, this system uses the autonomous control. For robot step climbing, the system uses the teleoperation mode.

3.1        Teleoperation

The robot is equipped with a camera, and the video imagery transmitted from it and the Motion Manager 5 operating window are displayed on the robot’s notebook PC. The screen on this notebook PC uses RealVNC (RealVCN Ltd., Cambridge, UK) software to transmit imagery as-is over the intranet to the display of the caretaker’s PC (robot operator). The caregiver can control the robot by operating Motion Manager 5 (Faulhaber-Global)from his PC. The caregiver and the wheelchair user both wear headsets. The caregiver’s headset is connected to his/her PC, and the chair user’s headset is connected to the robot PC via Bluetooth. The caregiver and the wheelchair user verbally telecommunicate via the Skype (Microsoft Corp., Redmond, Wa) communication application. Keyboard commands, which are activated by pushing the buttons of a joypad, correspond to the controller manipulations necessary to teleoperate the robot. Switching between teleoperation and autonomous control is carried out by the controller.

To lift the front wheels of the wheelchair, the robot stops while the wheelchair drive continues moving (see Section 4). However, network teleoperation is difficult for this process because the wheelchair’s raised front wheels tend to collide with the step when they are in near proximity with each other (Figure 11).

3.2        Autonomous control

An accelerometer system and an ultrasonic sensor system were added onto the chair, and a support system for the caregiver was created. The accelerometer system detects the incline of the chair, and the ultrasonic sensor system measures the distance between the chair and the step.

Both sensor systems are connected to the robot’s PC by a ZigBee wireless communication module. Since the support system for the caregiver is capable of performing the wheelchair step climbing process automatically, the caregiver (robot operator) does not need to control the vehicles in the autonomous control mode. However, the caregiver can watch the live video from the robot’s camera, and the wheelchair user and the caregiver are in direct verbal communication, so if the vehicles encountera problem,the caregiver switches from autonomous to teleoperation control to handle it.

Figure 11: Collision between the front wheels and step

4          Step climbing process

When the vehicles encounter a step, the robot hands grasp the rotary shaft of the wheelchair’s push handle mechanism, thus linking the two vehicles [14]. Joints 2, 4, and 6 are allowed to rotate passively (Figs. 5 and 8). In this study, Stages 1 and 2 signify the processes in which the wheelchair front and back wheels, respectively, ascend the step. Similarly, Stages 3 and 4 signify the processes in which the robot front and other wheels, respectively, climb the step.

Both vehicles move automatically during the wheelchair step climbing process (Stages 1 and 2) by using the caregiver’s support system. After that, the caregiver switches from autonomous control to teleoperation, and the robot step climbing process (Stage 3 and 4) is carried out. The ascent process is described below (the states shown in Figure 12 correspond to (1) through (16) below.

[Stage 1]

(1) From Stage 1 to Stage 2, the vehicles are under autonomous control. The wheelchair and the robot move forward until the ultrasonic sensor system detects a suitable position where the wheelchair front wheels do not collide with the step. (2) The robot stops and the wheelchair continues forward until the accelerometer system detects the wheelchair inclination level that would place the front wheels on the step. (3) At this point, the wheelchair center of mass is in front of the contact point between the rear wheels and the ground. If it shifts to behind the contact point as the wheelchair tilt increases, the stopper of the robot limits the passive rotation around Joint 2, which prevents the wheelchair from tipping over backward (Figure 6 (b)). (4) Both vehicles move forward, and the front wheels of the wheelchair are placed on the step.

[Stage 2]

(5) Both vehicles continue to move forward. (6) The back wheels of the wheelchair come into contact with the step. (7) The robot continues to push the wheelchair so that the rear wheels of the wheelchair climb up onto the step. The robot supports the wheelchair during this process to prevent the wheelchair from tipping over backward. (8) Both vehicles move forward, and the wheelchair’s rear wheels climb the step.

After the wheelchair’s rear wheels have reached the upper level of the step, the robot control mode is switched from autonomous to teleoperation control by the caregiver. The caregiver directs the vehicles to stop.

Figure 12: Step climbing process (Stages 1 through 4)

[Stage 3]

(9) The robot’s front and rear wheels are folded, its

sides are opened, and the manipulator forearm links are inserted into the wheelchair stopper (Figs. 8 (a) and (b)). The wheelchair stops while the robot moves forward, and the manipulator forearm links comes into contact with the front bars of the wheelchair stopper (Figure 9 (a)). (10) The robot continues to push the wheelchair using the forearm links, and the front wheels of the robot are lifted. (11) When the robot center of mass shifts behind the contact point between its middle and the ground, the robot’s tilt increases and it begins to tip over backward. However, at that point, part of the manipulator forearm links come into contact with the rear bars of wheelchair stopper, which limits the extent of rotation (Figure 9 (b)). Thus, the wheelchair prevents the robot from tipping over backward. (12) Both vehicles move forward, and the front wheels of the robot are placed on the upper level of the step.

[Stage 4]

(13) Both vehicles continue to move forward. (14) When the robot middle wheels come into contact with the step, the wheelchair pulls it forward. The robot rear wheels are lowered and provide climbing help. Then, the robot middle wheels begin to climb the step. (15) Both vehicles continue to move forward. (16) The robot middle wheels can now climb the step. Once the robot middle wheels have reached the upper level of the step, both vehicles are stopped, and the robot’s rear wheels are folded upward.

5          Theoretical Analysis

When the distance between the step and the wheelchair is too short to lift the front wheels, the wheels will collide with the step (Figure 11). In this section, we clarify the requirement for avoiding a collision between the chair front wheels and the step.

In Figure 13, Σ_B is the basic coordinate system for the robot and wheelchair, where p₀ is the origin as well as the contact position between the robot middle (driving) wheels and the ground. The position of the step edge is p_se, where p_i (i = 1–7) are the joints (p₁: axes of the robot middle wheels, p₂: shoulder joints, p₃: elbow joints, p₄: robot hands (location where the hands hold the wheelchair push handle), p₅: axes of the wheelchair rear wheels, p₆: axes of the wheelchair front wheels and, p₇: the tread of the wheelchair front wheels).

The position vectors for the joints in system Σ_B are expressed as ^B p_i = [x_i z_i]^T (i = 1 − 7). The position vectors of the step edge are ^B p_se = [L h]^T.

In the local coordinate system, in the case that Σ_i parallels Σ0, 0p1 = [0 RB]T, 1p2 = [lLB hLB]T, 2p3 = [l2 0]T,

3p4 = [l4C 0]T, 4p5 = [lLA −hLA]T, 5p6 = [lA −RA +rA]T, and ⁶p₇ = [r_A    0]^T (Figure 13).

Moreover, φ_i is the angle of Σ_i formed by Σ_i−1. In this system, φ₁ is zero in Stage 1 because Σ₁ parallels Σ₀, and φ₃ is zero when the wheelchair is pulled by the robot because the elbow joints are controlled passively. In addition, φ₅ = 0 is always zero because Σ₅ parallels Σ₄. Hence, the wheelchair inclination is Σ⁵_k=1φ_i = φ₂ + φ₄.

Σ_B(Σ₀)

Figure 13: Wheelchair and robot model

In the basic coordinate system Σ_B, the homogeneous transformation matrices ^BT₅, ^BT₆ are given below.

Here, φ₂₄ = φ₂ + φ₄, φ₂₄₆ = φ₂ + φ₄ + φ₆. Equations (3) and (4) show the positions of the wheelchair rear and front wheels axes, ^B p₅ = [x₅ y₅]^T, ^B p₆ = [x₆ y₆]^T, respectively.

B p5 : ” x₅ # = ” cosφ₂₄ −sinφ₂₄ #”  l_A                   # y5              sinφ24       cosφ24      −hLA

+ (l2 + l4C)cosφ2 # + ” lLB # (3) sinφ2 hLB + RB

B p6 : ” x6 # = ” cosφ24 −sinφ24 #” lA + lLA # y6 sinφ24 cosφ24 rA − RA − hLA

+ (l2 + l4C)cosφ2 # + ” lLB # (4) sinφ2 hLB + RB

Similarly, from a calculation of the transformation matrix ^BT₇, ^B p₇ = [x₇ y₇]^T is given below.

B p7 : ” x7 # = rA ” cosφ246 # y7            sinφ246

₊cosφ24 −sinφ24 #” lA + lLA # sinφ24 cosφ24 rA − RA − hLA

+ (l2 + l4C)cosφ2 # + ” lLB # (5) sinφ2 hLB + RB

Here, when ^B p₇ is the bottom position of the wheelchair front wheels, Σ⁶_k=1φ_i = −90 deg. Hence, cosφ₂₄₆ = 0 and sinφ₂₄₆ = −1.

Meanwhile, y₅ = R_A in Stage 1 because y₅ is the height of the wheelchair rear wheel axes (Figure 13). Hence, Equation (6) is obtained from (3).

lLA sinφ24−hLA cosφ24+(l2+l4C)sinφ2+hLB+RB = RA (6)

Thus,

hLA cosφ24 − lLA sinφ24 + RA − RB − hLB

        sinφ₂ =         (7)

l₂ + l₄C

and

                                   cosφ₂ = q1 − sin² φ₂                                                (8)

Equation (6) is substituted for y₇ of (5) when ^B p₇ is the bottom of the front wheels.

                y₇ = −r_A + l_A sinφ₂₄ + (−R_A + r_A)cosφ₂₄ + R_A                   (9)

where

                                  sinφ₂₄ = q1 − cos² φ₂₄                                          (10)

From Equations (9) and (10), we obtain Equation (11).

cosφ₂₄

(R_A − r_A)(R_A − r_A − y₇) + l_A p2(R_A − r_A)y₇ + l_A² − y₇²

=

(RA − rA)2 + lA2

(11)

We substitute y₇ = h for Equation (11) if the system detects the step height h, and can then ascertain the necessary minimum inclination of the wheelchair in order to put the front wheels on the step.

When the height of the front wheel axes is lower than the step height, the requirement needed to avoid a collision between the wheelchair front wheels and the step is Equation (12) (Figure 14 (a)).

                    k^B p_s −^Bp₆k > r_A (0 < x₆ < L, 0 < y₆ < h)               (12)

Here,

                                        B                                T

                                            p_s = [L y₆]                                      (13)

is a vector whose horizontal position is on the step wall (L), and the height is the same as the wheelchair front wheel axes (y₆).

Similarly, when the front wheel axes are above the step, Equation (14) shows the requirement to avoid a collision (Figure 14 (b)).

                       k^B p_se −^Bp₆k > r_A (0 < x₆ < L, h ≤ y₆)                 (14)

Then, using Equations (12) and (14), the system avoids a collision between the wheelchair front wheels and the step by detecting the chair inclination (φ₂ + φ₄), the distance from the step (L), and the step height (h).

Figure 14: Collision between the front wheels and a step.

(a) 0 ≤ y₆ ≤ h, (b) h < y₆

Figure 15: Step height and distance capable of avoiding

collision

The requirement for avoiding a collision between the wheelchair front wheels and the step (Equation (12), Figure 14 (a)) is more difficult than the case where the front wheel axes are above the step (Equation (14), Figure 14 (b)). Thus, we performed a numerical calculation to clarify the lifting position of the front wheels using Equation (12). Equation (12) is solved using (4), (7), (8), (10), (11), and (13). Here, y₇ is the minimum bottom height of the front wheels (Figure 13) needed for the system to lift the wheels up to the step height (h).

Substituting y₇ = h for Equation (12), the shading in Figure 15 shows a combination of the step height (h) and the distance (L) that enables it to avoid the collision, where the horizontal axis indicates h (step height) and the vertical axis indicates L (distance from the robot’s rear wheel axes to the step wall). By selecting the distance (L) in the shadings when the step height is (h), the wheelchair front wheels can avoid collision during climbing.

6          Experiment

An experiment was carried out in a situation involving a step 120 mm high and a friction coefficient µ = 0.72. The wheelchair user was on one floor of the National Institute of Technology, Toyama College, and the caregiver (robot operator) was on another floor. The movement speeds of the vehicles were constant (0.76 km/h). The wheelchair user and the robot operator were both able-bodied adult males. We assumed that the system knew the step height was below 120 mm.

In Stages 1 and 2, when using autonomous control, the wheelchair front wheels did not bump into the vertical wall of the step and the front wheels and rear wheels were able to traverse the step successfully (Figure 16). Here, L = 2.07 m. Operation changed from autonomous to teleoperation control following Stage 2, and the caregiver was able to move the robot forward into a suitable position for climbing the step. Next, the robot successfully climbed the step (Stages 3 and 4). In Stages 3 and 4, the system was operated by the caregiver who was watching video imagery from the robot’s camera. However, the operation was difficult because the robot inclined during its step climbing process and the mounted camera lost sight of the wheelchair. This and other experiments have shown that we need to construct a fully autonomous control system that can handle robot climbing as well as wheelchair climbing.

Figure 16: Step climbing experiment

7          Conclusion

This report describes a support system for a robot operator that can be used to perform wheelchair step climbing. The support system was designed and constructed in a way that permitted switching between teleoperation and autonomous control. We then conducted a theoretical analysis to show the requirements for preventing the wheelchair’s front wheels from colliding with the step, which involved a numerical calculation to clarify the position for lifting the wheelchair’s front wheels.

In experiments carried out with the system, autonomous control for wheelchair step climbing and teleoperation control for robot step climbing were both demonstrated to be effective. However, teleoperation control by a caregiver was complicated by the need to watch video imagery from the robot camera. This indicates that the system needs autonomous control system for the robot as well.

Nevertheless, it is notable that our theory for collision avoidance between the step wall and wheelchair’s front wheels during the step climbing was confirmed, and that both vehicles were able to climb a step using the theory and system.

In the future, we will construct a fully autonomous control system will be able to perform step climbing for both the wheelchair and the robot, and we will analyze a suitable step climbing trajectory for both vehicles.

Acknowledgment This research has been supported by the Kayamori Foundation of Informational Science Advancement (K25 XVII 430).

1. H. Ikeda, K. Hashimoto, D. Murayama, R. Yamazaki and E. Nakano, “Robot teleoperation support system for collision avoidance between heelchair front wheels and a step”, Proceedings of The 2016 IEEE International conference on Simulation, Modeling, and Programming for Autonomous Robots, 203-209, 2016.
2. V. Kumar and V. Krovi, “Optimal Traction Control In A Wheelchair With legs And Wheels”, Proceedings of the 4th National Applied Mechanisms and Robotics Conference, 95-030-01 – 95-030-07, 1995.
3. A.Gonzalez, E.Ottaviano and M.Ceccarelli “On the Kinematic Functionality of s Four-bar Based Mechanism for Guiding Wheels in Climbing Steps and Obstacles,” Mechanism and Machine Theory, 44, 1507-1523, 2009.
4. Independence Technology, L.L.C., iBOT, http://www.ibotnow.com/, 2008.
5. K.Sugiyama, T.Ishimatsu, T.Shigechi and M.Kurihara “Development of Staeir-climbing Machines at Nagasaki”, Proceedings of the 3rd International workshop of Advanced Mechatoronics, 214-217, 1999.
6. Y.Munakata and M.Wada, “Modeling and analysis of static wheelie of a five-wheeled wheelchair for climbing over a step”, Proceedings of IEEE/ASME International Conference on Advanced intelligent Mechatoronics, 1006-1011, 2014.
7. M.Lawn and T.Ishimatsu, “Modeling of a Stair-Climbing Wheelchair Mechanism with High Single Step Capability. IEEE Transactions on Neural Systems and Rehabilitation Engineering”, 11(3), 323-332, 2003.
8. Y. Mori, K. Katsumura, and K. Nagase. “A pair of step- climbing units for a manual wheelchair user: Passing over several steps using a pair of portable slopes”, Advances in Mechanical Engineering, 9(3), 1-11, 2017
9. H.Ikeda, Y.Katsumata, M.Shoji, T.Takahashi and E.Nakano “Cooperative strategy for a wheelchair and a robot to climb and descend a step,” ADVANCED ROBOTICS, 22, 1439- 1460, 2008.
10. H.Ikeda, H.Kanda, N.Yamashima and E.Nakano, “Step climbing and Descending for a Manual wheelchair with a Network care robot,”Proceeding of The Second International Conference on Intelligent System and Applications, 95-102, 2013.
11. H. Ikeda, N. Hatakeyama, A. Kinoshita and E.Nakano, “Step Moving for an Electric Wheelchair Using a Robot Programmable over the Intranet”, Proceedings of 2nd IEEE/SAE/IFAC International Conference on Connected Vehicles and Expo, 791-797, 2013.
12. H.Asama, M.Sato, N.Goto, H.Kaetsu, A.Matsumoto and I.Endo, “Mutual Transportation of Cooperative Mobile Robots Using Forklift Mechanisms,” Proceedings of the 1996 IEEE International Conference on Robotics and Automation, 1754-1759, 1996.
13. J. Gaston, K.Raahemifar, P.Hiscocks, “A cooperative Net- work of Reconfigurable Stair-Climbing Robots”, Proceeding of 2006 IEEE International Sysposium on circuits and Systems, 4-7, 2006.
14. H.Ikeda, N.Yamashima, S.Haruta and E.Nakano, “Docking method for a wheelchair and a care robot using both teleoperation and autonomous control”, International Journal of Machanical Engineering and Robotics Research, 5(2), 82- 89, 2016.

Citations by Dimensions

Citations by PlumX

Google Scholar

Crossref Citations

1. Jenna Snead, Nisa Soltani, Mia Wang, Joe Carson, Bailey Williamson, Kevin Gainey, Stanley McAfee, Qian Zhang, "3D Facial Feature Tracking with Multimodal Depth Fusion", Advances in Science, Technology and Engineering Systems Journal, vol. 10, no. 5, pp. 11–19, 2025. doi: 10.25046/aj100502
2. Woratida Sawangnamwong, Siam Charoenseang, "Assistive System for Collaborative Assembly Task using Augmented Reality", Advances in Science, Technology and Engineering Systems Journal, vol. 9, no. 4, pp. 110–118, 2024. doi: 10.25046/aj090412
3. Shuvo Kumar Paul, Mircea Nicolescu, Monica Nicolescu, "Integrating Speech and Gesture for Generating Reliable Robotic Task Configuration", Advances in Science, Technology and Engineering Systems Journal, vol. 9, no. 4, pp. 51–59, 2024. doi: 10.25046/aj090406
4. Traithep Wimonrut, Jittaboon Trichada, Narongsak Tirasuntarakul, Eakkachai Pengwang, "Design of Bio-Inspired Robot Hand Using Multiple Types of Actuators", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 6, pp. 65–77, 2023. doi: 10.25046/aj080608
5. Firdaus Sukarman, Ryoma Sato, Eisuke Kita, "Control Program Generator for Vehicle Robot using Grammatical Evolution", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 6, pp. 01–07, 2023. doi: 10.25046/aj080601
6. Lucksawan Yutthanakorn, Siam Charoenseang, "Augmented Reality Based Visual Programming of Robot Training for Educational Demonstration Site", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 5, pp. 8–16, 2023. doi: 10.25046/aj080502
7. Kohei Okawa, Felix Jimenez, Shuichi Akizuki, Tomohiro Yoshikawa, "Investigating the Impression Effects of a Teacher-Type Robot Equipped a Perplexion Estimation Method on College Students", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 4, pp. 28–35, 2023. doi: 10.25046/aj080404
8. Helmy Dewanto Bryantono, Melsiani Rosdiani Fillipin Saduk, Jiaqi Hong, Meng-Hsun Tsai, Shi-Chang Tseng, "Design and Manufacturing of Soft Grippers for Robotics by Injection Molding Technology", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 4, pp. 11–17, 2023. doi: 10.25046/aj080402
9. Mai Ngoc Anh, "Simulation of Obstacle Detection Based on Optical Flow Images for Avoidance Control of Mobile Robots", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 3, pp. 244–249, 2023. doi: 10.25046/aj080327
10. Xiuzhen Tang, Laliphat Manamanchaiyaporn, "Investigation of Swimming Behavior and Performance of the Soft Milli-Robots Embedded with Different Aspects of Magnetic Moments", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 3, pp. 193–201, 2023. doi: 10.25046/aj080322
11. Jittaboon Trichada, Traithep Wimonrut, Narongsak Tirasuntarakul, Eakkachai Pengwang, "Design of an Open Source Anthropomorphic Robotic Hand for Telepresence Robot", Advances in Science, Technology and Engineering Systems Journal, vol. 8, no. 1, pp. 17–29, 2023. doi: 10.25046/aj080103
12. Kohei Yamagishi, Tsuyoshi Suzuki, "Regular Tessellation-Based Collective Movement for a Robot Swarm with Varying Densities, Scales, and Shapes", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 6, pp. 31–38, 2022. doi: 10.25046/aj070604
13. Hiroaki Hanai, Akira Mishima, Atsuyuki Miura, Toshiki Hirogaki, Eiichi Aoyama, "Realization of Skillful Musical Saw Bowing by Industrial Collaborative Humanoid Robot", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 5, pp. 1–9, 2022. doi: 10.25046/aj070501
14. Dinh Manh Hung, Dang Xuan Ba, "A Constrained Intelligent Nonlinear Control Method for Redundant Robotic Manipulators", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 3, pp. 174–181, 2022. doi: 10.25046/aj070320
15. Heidi Fleischer, Sascha Statkevych, Janne Widmer, Regina Stoll, Thomas Roddelkopf, Kerstin Thurow, "Automated Robotic System for Sample Preparation and Measurement of Heavy Metals in Indoor Dust Using Inductively Coupled Plasma Mass Spectrometry (ICP-MS)", Advances in Science, Technology and Engineering Systems Journal, vol. 7, no. 3, pp. 139–151, 2022. doi: 10.25046/aj070316
16. Hideya Yoshiuchi, Tomohiro Matsuda, "Service Robot Management System for Business Improvement and Service Extension", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 6, pp. 34–42, 2021. doi: 10.25046/aj060606
17. Indravash Chowdhury, Ravinder Singh, Christopher Kluse, Mohammad Mayyas, "The Effect of Obstacle Design Architectures on Randomly Ranging AGVs in a Shared Workspace", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 5, pp. 335–347, 2021. doi: 10.25046/aj060538
18. Ngoc-Anh Mai, "Modelling and Simulation of Fuzzy-based Coordination of Trajectory Planning and Obstacle Avoiding for RRP-Typed SCARA Robots", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 4, pp. 348–354, 2021. doi: 10.25046/aj060439
19. Márcio Mendonça, Rodrigo Henrique Cunha Palácios, Ivan Rossato Chrun, Diene Eire de Mello, Henrique Cavalieri Agonilha, Elpiniki Papageorgiou, Konstantinos Papageorgiou, "Initial Experiments using Game-based Learning Applied in a Classical Knowledge Robotics in In-Person and Distance Learning Classroom", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 4, pp. 212–222, 2021. doi: 10.25046/aj060425
20. Ahmed R. Sadik, Christian Goerick, "Multi-Robot System Architecture Design in SysML and BPMN", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 4, pp. 176–183, 2021. doi: 10.25046/aj060421
21. Dimitris Ziouzios, Pavlos Kilintzis, Nikolaos Baras, Minas Dasygenis, "A Survey of FPGA Robotics Applications in the Period 2010 – 2019", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 3, pp. 385–408, 2021. doi: 10.25046/aj060344
22. Suchada Sitjongsataporn, Kornika Moolpho, Sethakarn Prongnuch, "Gripper Finger Design for Automatic Bottle Opener", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 1065–1073, 2021. doi: 10.25046/aj0602121
23. Hyeongjoo Kim, Sunyong Byun, "Designing and Applying a Moral Turing Test", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 93–98, 2021. doi: 10.25046/aj060212
24. Auttapoom Loungthongkam, Chana Raksiri, "The Analysis of Standard Uncertainty of Six Degree of Freedom (DOF) Robot", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 43–50, 2021. doi: 10.25046/aj060206
25. Laurent Nana, François Monin, Sophie Gire, "Formal Proof of Properties of a Syntax-Oriented Editor of Robotic Missions Plans", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 1049–1057, 2021. doi: 10.25046/aj0601116
26. José Paulo de Almeida Amaro, João Manuel Leitão Pires Caldeira, Vasco Nuno da Gama de Jesus Soares, João Alfredo Fazendeiro Fernandes Dias, "Autonomous Robot Path Construction Prototype Using Wireless Sensor Networks", Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 1, pp. 169–177, 2021. doi: 10.25046/aj060119
27. Abubakar Umar, Zhanqun Shi, Lin Zheng, Alhadi Khlil, Zulfiqar Ibrahim Bibi Farouk, "Parameter Estimation for Industrial Robot Manipulators Using an Improved Particle Swarm Optimization Algorithm with Gaussian Mutation and Archived Elite Learning", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 6, pp. 1436–1457, 2020. doi: 10.25046/aj0506174
28. Sasithorn Chookaew, Suppachai Howimanporn, Santi Hutamarn, "Investigating Students’ Computational Thinking through STEM Robot-based Learning Activities", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 6, pp. 1366–1371, 2020. doi: 10.25046/aj0506164
29. Le Duc Hanh, Huynh Buu Tu, "Computer Vision for Industrial Robot in Planar Bin Picking Application", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 6, pp. 1244–1249, 2020. doi: 10.25046/aj0506148
30. Dang Xuan Ba, "A Fast Adaptive Time-delay-estimation Sliding Mode Controller for Robot Manipulators", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 6, pp. 904–911, 2020. doi: 10.25046/aj0506107
31. Mikhail Vladimirovich Vartanov, Trung Ta Tran, Van Dung Nguyen, "Research of the Effect of Rotation and Low-Frequency Vibration on the Robotic Assembly Process", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 6, pp. 160–168, 2020. doi: 10.25046/aj050619
32. Victoria Oguntosin, Akindele Ayoola E, "Control of Soft Robotic Artificial Muscle with Hand Gesture Using Leap Motion Sensor", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 5, pp. 1007–1012, 2020. doi: 10.25046/aj0505123
33. Kanjanapan Sukvichai, Kan Yajai, "Design of a Flapping Wings Butterfly Robot based on Aerodynamics Force", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 4, pp. 667–675, 2020. doi: 10.25046/aj050480
34. Pham Van Bach Ngoc, Le Thi Hong Gam, Dam Hai Quan, Bui Trung Thanh, Nguyen Luong Thien, "Modelling and Simulation of 3-DOF Lower Limb Rehabilitation Robot using Force Feed Forward Control", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 4, pp. 626–632, 2020. doi: 10.25046/aj050474
35. Mohammed Qbadou, Intissar Salhi, Hanaâ El fazazi, Khalifa Mansouri, Michail Manios, Vassilis Kaburlasos, "Human-Robot Multilingual Verbal Communication – The Ontological knowledge and Learning-based Models", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 4, pp. 540–547, 2020. doi: 10.25046/aj050464
36. Thongchai Disyadej, Surat Kwanmuang, Paisarn Muneesawang, Jatuporn Promjan, Kanyuta Poochinapan, "Smart Transmission Line Maintenance and Inspection using Mobile Robots", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 3, pp. 493–500, 2020. doi: 10.25046/aj050361
37. Efrain Mendez, German Baltazar-Reyes, Israel Macias, Adriana Vargas-Martinez, Jorge de Jesus Lozoya-Santos, Ricardo Ramirez-Mendoza, Ruben Morales-Menendez and Arturo Molina, "ANN Based MRAC-PID Controller Implementation for a Furuta Pendulum System Stabilization", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 3, pp. 324–333, 2020. doi: 10.25046/aj050342
38. Rajesh Kannan Megalingam, Raviteja Geesala, Ruthvik Rangaiah Chanda, Nigam Katta, "Multimode Control and Simulation of 6-DOF Robotic Arm in ROS", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 3, pp. 306–316, 2020. doi: 10.25046/aj050340
39. Rajesh Kannan Megalingam, Deepak Nagalla, Ravi Kiran Pasumarthi, Vamsi Gontu, Phanindra Kumar Allada, "Angular Orientation of Steering Wheel for Differential Drive", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 3, pp. 275–283, 2020. doi: 10.25046/aj050336
40. Noraziah Adzhar, Yuhani Yusof, Muhammad Azrin Ahmad, "A Review on Autonomous Mobile Robot Path Planning Algorithms", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 3, pp. 236–240, 2020. doi: 10.25046/aj050330
41. Rajesh Kannan Megalingam, Santosh Tantravahi, Hemanth Sai Surya Kumar Tammana, Nagasai Thokala, Hari Sudarshan Rahul Puram, Naveen Samudrala, "ROS Based Multimode Control of Wheeled Robot", Advances in Science, Technology and Engineering Systems Journal, vol. 5, no. 2, pp. 688–696, 2020. doi: 10.25046/aj050285
42. Daniel Szabo, Emese Gincsaine Szadeczky-Kardoss, "Novel Cost Function based Motion-planning Method for Robotic Manipulators", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 6, pp. 386–396, 2019. doi: 10.25046/aj040649
43. Ahmad Yusairi Bani Hashim, Silah Hayati Kamsani, Mahasan Mat Ali, Syamimi Shamsuddin, Ahmad Zaki Shukor, "Simulation and Reproduction of a Manipulator According to Classical Arm Representation and Trajectory Planning", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 6, pp. 158–162, 2019. doi: 10.25046/aj040619
44. Ha Quang Thinh Ngo, Thanh Phuong Nguyen, Hung Nguyen, "The Fusing Framework Between Lifting Carrier and Tractor-Trailer for Modern Transportation", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 4, pp. 522–528, 2019. doi: 10.25046/aj040463
45. Mohamad Faiz Ahmad, Syed Sahal Nazli Alhady, Ooi Zhu Oon, Wan Amir Fuad Wajdi Othman, Aeizaal Azman Abdul Wahab, Ahmad Afiq Muhammad Zahir, "Embedded Artificial Neural Network FPGA Controlled Cart", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 4, pp. 509–516, 2019. doi: 10.25046/aj040461
46. Maryam Butt, Golshah Naghdy, Fazel Naghdy, Geoffrey Murray, Haiping Du, "Investigating The Detection of Intention Signal During Different Exercise Protocols in Robot-Assisted Hand Movement of Stroke Patients and Healthy Subjects Using EEG-BCI System", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 4, pp. 300–307, 2019. doi: 10.25046/aj040438
47. Anna Lekova, Ivan Chavdarov, Bozhidar Naydenov, Aleksandar Krastev, Snezhanka Kostova, "Brain-inspired IoT Controlled Walking Robot – Big-Foot", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 3, pp. 220–226, 2019. doi: 10.25046/aj040329
48. Rung-Shiang Cheng, Wei-Jun Hong, Jhe-Lin Li, Kawuu W. Lin, "Indoor Positioning and Path Planning Platform for iRobot Create 2 Sweeping Robot", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 3, pp. 198–206, 2019. doi: 10.25046/aj040327
49. Yuhei Tanizaki, Felix Jimenez, Tomohiro Yoshikawa, Takeshi Furuhashi, Masayoshi Kanoh, "Effects of Educational Support Robots using Sympathy Expression Method with Body Movement and Facial Expression on the Learners in Short and Long-term Experiments", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 2, pp. 183–189, 2019. doi: 10.25046/aj040224
50. Gabriel Dämmer, Sven Gablenz, Alexander Hildebrandt, Zoltan Major, "Design of an Additively Manufacturable Multi-Material Light-Weight Gripper with integrated Bellows Actuators", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 2, pp. 23–33, 2019. doi: 10.25046/aj040204
51. Konstantin Mironov, Ruslan Gayanov, Dmiriy Kurennov, "Observing and Forecasting the Trajectory of the Thrown Body with use of Genetic Programming", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 1, pp. 248–257, 2019. doi: 10.25046/aj040124
52. Samuel Oludare Bamgbose, Xiangfang Li, Lijun Qian, "Trajectory Tracking Control Optimization with Neural Network for Autonomous Vehicles", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 1, pp. 217–224, 2019. doi: 10.25046/aj040121
53. Fang-Lin Chao, Hung-Chi Chu, Liza Lee, "Robot-Assisted Posture Emulation for Visually Impaired Children", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 1, pp. 193–199, 2019. doi: 10.25046/aj040119
54. Daniel M. Lofaro, Magdalena Bugajska, Donald Sofge, "Extending the Life of Legacy Robots: MDS-Ach via x-Ach", Advances in Science, Technology and Engineering Systems Journal, vol. 4, no. 1, pp. 50–72, 2019. doi: 10.25046/aj040107
55. Ivaylo Penev, Milena Karova, Mariana Todorova, Danislav Zhelyazkov, "Robot Self-Detection System", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 6, pp. 391–402, 2018. doi: 10.25046/aj030647
56. Paolo Mercorelli, "Using Fuzzy PD Controllers for Soft Motions in a Car-like Robot", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 6, pp. 380–390, 2018. doi: 10.25046/aj030646
57. Jorge Alejandro Kamlofsky, Nicol Naidoo, Glen Bright, Maria Lorena Bergamini, Jose Zelasco, Francisco Ansaldo, Riaan Stopforth, "Semi-Autonomous Robot Control System with an improved 3D Vision Scheme for Search and Rescue Missions. A joint research collaboration between South Africa and Argentina", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 6, pp. 347–357, 2018. doi: 10.25046/aj030643
58. Elena Basan, Alexander Basan, Oleg Makarevich, "Probabilistic Method for Anomalies Detection Based on the Analysis of Cyber Parameters in a Group of Mobile Robots", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 6, pp. 281–288, 2018. doi: 10.25046/aj030636
59. Wafa Ghozlane, Jilani Knani, "NonLinear Control via Input-Output Feedback Linearization of a Robot Manipulator", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 5, pp. 374–381, 2018. doi: 10.25046/aj030543
60. Jia-Jing Kao, Chun-Liang Lin, Chih-Cheng Huang, Hau-Shian Jian, "Contactless Power and Bidirectional Data Transmission via Magnetic Field", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 5, pp. 226–234, 2018. doi: 10.25046/aj030528
61. Mohammed Faeik Ruzaij Al-Okby, Sebastian Neubert, Norbert Stoll, Kerstin Thurow, "Development and Testing of Intelligent Wheelchair Controller for Quadriplegic Patients", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 5, pp. 220–225, 2018. doi: 10.25046/aj030527
62. Eiken Lübbers, Dierk Schoen, "Implementation of a Robot Contest for Distance Education", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 5, pp. 161–165, 2018. doi: 10.25046/aj030520
63. Andre Dehne, Nantwin Moller, Thorsten Hermes, "MARWIN: Localization of an Inspection Robot in a Radiation exposed Environment", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 4, pp. 354–362, 2018. doi: 10.25046/aj030436
64. Hung Chan Nguyen, Ha Xuan Nguyen, Ngoc-Anh Maia, Lam Bao Dang, and Hai Minh Pham, "A modular design process for developing humanoid mobile robot VieBot", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 4, pp. 230–235, 2018. doi: 10.25046/aj030422
65. Emese Gincsainé Szádeczky-Kardoss, Zoltán Gyenes, "Velocity obstacles for car-like mobile robots: Determination of colliding velocity and curvature pairs", Advances in Science, Technology and Engineering Systems Journal, vol. 3, no. 1, pp. 225–233, 2018. doi: 10.25046/aj030127
66. Yoshiki Iwamochi, Motoki Takagi, Tasuku Miyoshi, "Flexible lengthening-shortening arm mechanism for fishery resource management", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 6, pp. 290–301, 2017. doi: 10.25046/aj020636
67. Ali Abduljalil Abdulla, Hui Liu, Norbert Stoll, Kerstin Thurow, "A Secure Automated Elevator Management System and Pressure Sensor based Floor Estimation for Indoor Mobile Robot Transportation", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1599–1608, 2017. doi: 10.25046/aj0203199
68. Vivekananda Shanmuganatha, Lad Pranav Pratap, Pawar Mansi Shailendrasingh, "Modeling and Control of Collaborative Robot System using Haptic Feedback", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1549–1555, 2017. doi: 10.25046/aj0203193
69. Alex Masuo Kaneko, Kenjiro Yamamoto, "Monocular Height Estimation Method with 3 Degree-Of-Freedom Compensation of Road Unevennesses", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1443–1452, 2017. doi: 10.25046/aj0203180
70. Mohammed Myasar Ali, Hui Liu, Norbert Stoll, Kerstin Thurow, "Grasping and Placing Operation for Labware Transportation in Life Science Laboratories using Mobile Robots", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1227–1237, 2017. doi: 10.25046/aj0203155
71. Mohammed Myasar Ali, Hui Liu, Norbert Stoll, Kerstin Thurow, "Recognition and Position Estimation for Multiple Labware Transportation Using Kinect V2 and Mobile Robots", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 1218–1226, 2017. doi: 10.25046/aj0203154
72. Taha Beyrouthy, Samer Al Kork, Joe Akl Korbane, Mohamed Abouelela, "EEG Mind Controlled Smart Prosthetic Arm – A Comprehensive Study", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 891–899, 2017. doi: 10.25046/aj0203111
73. Mohammed Faeik Ruzaij Al-Okby, Sebastian Neubert, Norbert Stoll, Kerstin Thurow, "Low-cost Hybrid Wheelchair Controller for Quadriplegias and Paralysis Patients", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 687–694, 2017. doi: 10.25046/aj020388
74. Mazen Ghandour, Hui Liu, Norbert Stoll, Kerstin Thurow, "Human Robot Interaction for Hybrid Collision Avoidance System for Indoor Mobile Robots", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 650–657, 2017. doi: 10.25046/aj020383
75. Fatma Abdelhedi, Nabil Derbel, "A delay-dependent distributed SMC for stabilization of a networked robotic system exposed to external disturbances", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 513–519, 2017. doi: 10.25046/aj020366
76. Khalid Al-Mutib, Foudil Abdessemed, "Indoor Mobile Robot Navigation in Unknown Environment Using Fuzzy Logic Based Behaviors", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 327–337, 2017. doi: 10.25046/aj020342
77. Marwa Fathallah, Fatma Abdelhedi, Nabil Derbel, "A synchronizing second order sliding mode control applied to decentralized time delayed multi-agent robotic systems: Stability Proof", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 3, pp. 160–170, 2017. doi: 10.25046/aj020321
78. Sender Rocha dos Santos, Jorge L. M. Amaral, José Franco M. Amaral, "Adaptive Intelligent Systems applied to two-wheeled robot and the effect of different terrains on performance", Advances in Science, Technology and Engineering Systems Journal, vol. 2, no. 1, pp. 1–5, 2017. doi: 10.25046/aj020101