# Hardware Development and Safety Control Strategy Design for a Mobile Rehabilitation Robot
###### Abstract  
The use of bodyweight unloading force control on a treadmill with therapist manual assistance for gait training imposes constraints on natural walking. It influences the patient's training effect for a full range of natural walks. This study presents a prototype and a safety controller for a mobile rehabilitation robot (MRR). The prototype integrates an autonomous mobile bodyweight support system (AMBSS) with a lower-limb exoskeleton system (LES) to simultaneously achieve natural over-ground gait training and motion relearning. Human-centered rehabilitation robots must guarantee the safety of patients in the presence of significant tracking errors. It is difficult for traditional stiff controllers to ensure safety and excellent tracking accuracy concurrently, because they cannot explicitly guarantee smooth, safe, and overdamped motions without overshoot. This paper integrated a linear extended state observer (LESO) into proxy-based sliding mode control (ILESO-PSMC) to overcome this problem. The LESO was used to observe the system's unknown states and total disturbance simultaneously, ensuring that the \"proxy\" tracks the reference target accurately and avoids the unsafe control of the MRR. Based on the Lyapunov theorem to prove the closed-loop system stability, the proposed safety control strategy has three advantages: (1) it provides an accurate and safe control without worsening tracking performance during regular operation, (2) it guarantees safe recoveries and overdamped properties after abnormal events, and (3) it need not identify the system model and measure unknown system states as well as external disturbance, which is quite difficult for human-robot interaction (HRI) systems. The results demonstrate the feasibility of the proposed ILESO-PSMC for MRR. The experimental comparison also indicates better safety performance for the ILESO-PSMC than for the conventional proportional-integral-derivative (PID) control. p 202  
to help users accomplish their desired activities. Orthoses and exoskeletons represent two prime examples of wearable robotics. They can be \"worn\" by the operator, fit snugly on the body, and work in harmony with the operator's movements. The distinction between orthoses and exoskeletons is blurry. The term \"exoskeleton\" refers to systems, not just passive protection and support shells. Among these exoskeleton rehabilitation systems, wearable rehabilitation robots related to the lower limbs are an essential part, because the lower limbs of the human are one of the most critical parts in maintaining autonomy in life [1]. These exoskeleton rehabilitation devices drive subjects to repeatedly move their upper or lower limbs along a given trajectory. The control strategies combined with the assist-as-needed method enable the gait rehabilitation exoskeleton to improve its training efficiency [2]. Continuous passive motion (CPM) uses exoskeleton systems to substitute for physical therapists; it is an effective gait training method for treating limb spasticity and contractures [3]. The CPM can effectively improve the effectiveness of rehabilitation training [4]. The use of exoskeleton devices in the rehabilitation process enables precise, controlled, and long-term training. However, rigid exoskeletons still have issues such as safety, adaptability, and comfort that need to be overcome during the rehabilitation process. Therefore, the development of rehabilitation exoskeletons is gradually shifting towards soft exoskeletons [5; 6]. Patients trained with robotic assistance combined with physical therapy have a better chance of walking independently than those who did not use mechanical aid [7]. Relative motion-based treadmill gait training systems, such as GaitTrainer [1], LOPES [8], ALEX [9], and Lokomat [10] are frequently integrated with the bodyweight support system (BSS) and lower limb exoskeletons to realize CPM. These systems use active, passive, and damping training modes to repeat high-intensity training.