Abstract-The development of dynamic rehabilitation devices can be evaluated as a research fastgrowing field. Indeed, robot-assisted therapy is an advanced new technology mainly in stroke rehabilitation. Although patients benefit from this enormous development of technology, including the presence of rehabilitation robots, the therapeutic field still suffering a lack in hand robotic rehabilitation devices. In this context, this work proposes a new design of a 3D printed hand exoskeleton for the stroke rehabilitation. Based on the EMG signals measured from the muscles responsible for the hand motion, the designed mechatronic system detects the intention of hand opening or hand closing from the stroked subject. Based on an embedded controller and five servomotors, the low cost robotic system is able to drive in real time three degrees of freedom (DOFs) for each finger. The real tests with stroked subjects showed that the designed hand exoskeleton architecture has a positive effect on the motion finger range and mainly in the hand ability to perform some simple tasks. The case studies showed a good recovery of the motor functions and consequently the developed system efficiency.

Currently, the path planning problem is one of the most researched topics in autonomous robotics. That is why finding a safe path in a cluttered environment for a mobile robot is an important requirement for the success of any such mobile robot project. In this work, a developed algorithm based on free segments and a turning point strategy for solving the problem of robot path planning in a static environment is presented. The aim of the turning point approach is to search a safe path for the mobile robot, to make the robot moving from a starting position to a destination position without hitting obstacles. This proposed algorithm handles two different objectives which are the path safety and the path length. In addition, a robust control law which is called sliding mode control is proposed to control the stabilization of an autonomous mobile robot to track a desired trajectory. Finally, simulation results show that the developed approach is a good alternative to obtain the adequate path and demonstrate the efficiency of the proposed control law for robust tracking of the mobile robot.

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Recently, the technological development of manipulator robot increases very quickly and provides a positive impact to human life. The implementation of the manipulator robot technology offers more efficiency and high performance for several human’s tasks. In reality, efforts published in this context are focused on implementing control algorithms with already preprogrammed desired trajectories (passive robots case) or trajectory generation based on feedback sensors (active robots case). However, gesture based control robot can be considered as another channel of system control which is not widely discussed. This paper focuses on a Kinect-based real-time interactive control system implementation. Based on LabVIEW integrated development environment (IDE), a developed human-machine-interface (HMI) allows user to control in real time a Lynxmotion robotic arm. The Kinect software development kit (SDK) provides a tool to keep track of human body skeleton and abstract it into 3-dimensional coordinates. Therefore, the Kinect sensor is integrated into our control system to detect the different user joints coordinates. The Lynxmotion dynamic has been implemented in a real-time sliding mode control algorithm. The experimental results are carried out to test the effectiveness of the system, and the results verify the tracking ability, stability, and robustness.

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Abstract-Generally, the rehabilitation process needs a physical interactions between patients and therapists. Based on the principles governing such human-human interactions (HHI), the design of rehabilitation robots received several attempts in order to abstract the HHI in human-robot interaction (HRI). To achieve this goal, the rehabilitation robot should be smart and provides a useful and comprehensive platform to track the patient status. In this paper, a biofeedback-based high fidelity smart robot for wrist rehabilitation is designed. This robot is intended for repetitive exercises without