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Spinal cord stimulation (SCS) is primarily utilized for pain management and has recently demonstrated efficacy in promoting functional recovery in patients with spinal cord injury. Effective stimulation of motor neurons ideally requires the…
We are motivated by the real challenges presented in a human-robot system to develop new designs that are efficient at data level and with performance guarantees such as stability and optimality at systems level. Existing…
Hybrid assistive systems that integrate functional electrical stimulation (FES) and robotic exoskeletons offer a promising approach for neurorehabilitation. However, control of these systems remains challenging due to actuator redundancy…
Recurrent neural network-based reinforcement learning systems are capable of complex motor control tasks such as locomotion and manipulation, however, much of their underlying mechanisms still remain difficult to interpret. Our aim is to…
Wearable devices like exoskeletons are designed to reduce excessive loads on specific joints of the body. Specifically, single- or two-degrees-of-freedom (DOF) upper-body industrial exoskeletons typically focus on compensating for the…
We propose a robust dynamic walking controller consisting of a dynamic locomotion planner, a reinforcement learning process for robustness, and a novel whole-body locomotion controller (WBLC). Previous approaches specify either the position…
Complicated first principles modelling and controller synthesis can be prohibitively slow and expensive for high-mix, low-volume products such as hydraulic excavators. Instead, in a data-driven approach, recorded trajectories from the real…
Balance control is important for human and bipedal robotic systems. While dynamic balance during locomotion has received considerable attention, quantitative understanding of static balance and falling remains limited. This work presents a…
Purpose: Research has revealed that strength training can reduce the incidence of chronic diseases and physical deterioration at any age. Therefore, having a movement diagnostic system is crucial for training alone. Hence, this study…
For the deployment of legged robots in real-world environments, it is essential to develop robust locomotion control methods for challenging terrains that may exhibit unexpected deformability and irregularity. In this paper, we explore the…
This paper studies the container lifting phase of a waste-container recycling task in urban environments, performed by a hydraulic loader crane equipped with an underactuated discharge unit, and proposes a residual reinforcement learning…
In the realm of exoskeleton control, achieving precise control poses challenges due to the mechanical delay of exoskeletons. To address this, incorporating future gait trajectories as feed-forward input has been proposed. However, existing…
Current control strategies for powered lower limb prostheses often lack awareness of the environment and the user's intended interactions with it. This limitation becomes particularly apparent in complex terrains. Obstacle negotiation, a…
Skeleton-based Human Activity Recognition has achieved great interest in recent years as skeleton data has demonstrated being robust to illumination changes, body scales, dynamic camera views, and complex background. In particular,…
This paper presents a novel approach to evaluating back support exoskeletons (BSEs) in workplace settings addressing the limitations of traditional methods like electromyography (EMG), which are impractical due to their sensitivity to…
Robotic systems are increasingly used in rehabilitation to provide high intensity training for patients with motor impairment. The results of controlled trials involving human subjects confirm the effectiveness of robot-enhanced methods and…
Physics-based character animation has become a fundamental approach for synthesizing realistic, physically plausible motions. While current data-driven deep reinforcement learning (DRL) methods can synthesize complex skills, they struggle…
In this work, we introduce the principle, design and mechatronics of Exo-Muscle, a novel assistive device for the knee joint. Different from the existing systems based on rigid exoskeleton structures or soft-tendon driven approaches, the…
Energy efficiency and low latency are crucial requirements for designing wearable AI-empowered human activity recognition systems, due to the hard constraints of battery operations and closed-loop feedback. While neural network models have…
Current exoskeleton control methods often face challenges in delivering personalized treatment. Standardized walking gaits can lead to patient discomfort or even injury. Therefore, personalized gait is essential for the effectiveness of…