Robot-assisted therapy has become increasingly popular and useful in post-stroke neurorehabilitation. This paper presents an overview of the design and control of the dual-arm Recupera exoskeleton to provide intense therapist-guided as well as self training for sensorimotor rehabilitation of the upper body. The exoskeleton features a lightweight design, high level of modularity, decentralized computing, and various levels of safety implementation. Due to its modularity, the system can be used as a wheel-chair mounted system or as a full-body system. Both systems enable a wide range of therapies while efficiently grounding the weight of the system and without compromising the patient’s mobility. Furthermore, two rehabilitation therapies implemented on the exoskeleton system, namely teach & replay therapy and mirror therapy, are presented along with experimental results.

Exoskeleton robots are electrically, pneumatically, or hydraulically actuated devices that externally support the bones and cartilage of the human body while trying to mimic the human movement capabilities and augment muscle power. The lower extremity exoskeleton device may support specific human joints such as hip, knee, and ankle, or provide support to carry and balance the weight of the full upper body. Their assistive functionality for physically-abled and disabled humans is demanded in medical, industrial, military, safety applications, and other related fields. The vision of humans walking with an exoskeleton without external support is the prospect of the robotics and artificial intelligence working groups. This paper presents a survey on the design and control of lower extremity exoskeletons for bipedal walking. First, a historical view on the development of walking exoskeletons is presented and various lower body exoskeleton designs are categorized in different application areas. Then, these designs are studied from design, modeling, and control viewpoints. Finally, a discussion on future research directions is provided.

Parallel mechanisms are increasingly being used as modular subsystem units in various robots and man-machine interfaces for their superior stiffness, payload-to-weight ratio, and dynamic properties. This leads to series-parallel hybrid robotic systems that are challenging to model and control due to the presence of various closed loops. Most model-based kinematic and dynamic modeling tools resolve loop closure constraints numerically and hence suffer from inefficiency and accuracy issues. Additionally, they do not exploit the modularity in robot design. In this paper, we present a modular and analytical approach toward kinematic and dynamic modeling of series-parallel hybrid robots. This approach has been implemented in a software framework called hybrid robot dynamics (hyrodyn) and its application is demonstrated with the help of a series-parallel hybrid humanoid robot recently developed at DFKI-RIC.