Multimodal fusion and human-robot interaction control of an intelligent robot - Gong, Tao; Chen, Dan; Wang, Guangping; Zhang, Weicai; Zhang, Junqi; Ouyang, Zhongchuan; Zhang, Fan; Sun, Ruifeng; Ji, Jiancheng Charles; Chen, Wei (Frontiers in Bioengineering and Biotechnology, 2024)
The small-scaled robotic walkers play an increasingly important role in the Activity of Daily Living (ADL) assistance in the face of ever-increasing rehab requirements and existing equipment's drawback. This paper proposes a Rehabilitation Robotic Walker (RRW) for walking assistance and body weight support (BWS) during the gait rehabilitation. The walker provides the patients with weight offloading and guiding force to mimic a series of the PT movements, and creates a natural, comfortable and reassured environment. This system is consisted of an omni-directional mobile platform, a BWS mechanism and a pelvic brace to smooth the motions of pelvis. To recognize the human intentions, four force sensors, two joysticks and one depth-sensing camera were used to monitor the man-machine information, and a multimodal fusion algorithm for intention recognition was proposed to improve the accuracy. Then the system obtained the heading angle E, the pelvic pose F and the motion vector H via the camera, the force sensors and the joysticks respectively, classified the intentions with feature extraction and information fusion, finally outputted the motor speed control through the robot kinematics. To validate the validity of the algorithm above, a preliminary test with three volunteers was conducted to study the motion control. The results showed that the average error of the integral square error (ISE) was 2.90 and minimum error was 1.96, which demonstrated that the efficiency of the proposed method and the system is capable of providing walking assistance.