Computational Synthesis of Wearable Robot Mechanisms: Application to Hip-Joint Mechanisms

Since wearable linkage mechanisms could control the moment transmission from actuator(s) to wearers, they can help ensure that even low-cost wearable systems provide advanced functionality tailored to users' needs. For example, if a hip mechanism transforms an input torque into a spatially-varying moment, a wearer can get effective assistance both in the sagittal and frontal planes during walking, even with an affordable single-actuator system. However, due to the combinatorial nature of the linkage mechanism design space, the topologies of such nonlinear-moment-generating mechanisms are challenging to determine, even with significant computational resources and numerical data. Furthermore, on-premise production development and interactive design are nearly impossible in conventional synthesis approaches. Here, we propose an innovative autonomous computational approach for synthesizing such wearable robot mechanisms, eliminating the need for exhaustive searches or numerous data sets. Our method transforms the synthesis problem into a gradient-based optimization problem with sophisticated objective and constraint functions while ensuring the desired degree of freedom, range of motion, and force transmission characteristics. To generate arbitrary mechanism topologies and dimensions, we employed a unified ground model. By applying the proposed method for the design of hip joint mechanisms, the topologies and dimensions of non-series-type hip joint mechanisms were obtained. Biomechanical simulations validated its multi-moment assistance capability, and its wearability was verified via prototype fabrication. The proposed design strategy can open a new way to design various wearable robot mechanisms, such as shoulders, knees, and ankles.Comment: 28 pages, 7 figures, Supplementary Material

Smart Exercise Adaptive Control of a Three Degree of Freedom Upper-limb Manipulator Robot

An adaptive velocity field controller for robotic manipulators is proposed in this thesis. The control objective is to cause the user to exercise in a manner that optimizes a criterion related to the user’s mechanical power. The control structure allows for passive user-manipulator physical interaction while the adaptive algorithm identifies the user’s biomechanical characteristics as a linear Hill based force-velocity curve defined at each pose of a repetitive exercise motion i.e. a Hill surface. The study of such a surface allows for the characterization of maximal effort exercise tasks and subsequently the control of exercises that is unique to each user. This allows for the intelligent characterization of a user’s abilities such that repetitive exercises defined by velocity fields can be safely performed. Such a study involving a 3DOF manipulator operating in full 3D has not been conducted in literature to the best of author’s knowledge. The proposed control structure is verified through experimentation on a unimanual setup of the BURT rehabilitation manipulator system involving a single user. The manipulator system includes friction, actuator/sensor noise, and unmodelled dynamics