Redundancy resolution of a human arm for controlling a seven DOF wearable robotic system

A survey of human shoulder functional kinematic representations

In this survey, we review the field of human shoulder functional kinematic representations. The central question of this review is to evaluate whether the current approaches in shoulder kinematics can meet the high-reliability computational challenge. This challenge is posed by applications such as robot-assisted rehabilitation. Currently, the role of kinematic representations in such applications has been mostly overlooked. Therefore, we have systematically searched and summarised the existing literature on shoulder kinematics. The shoulder is an important functional joint, and its large range of motion (ROM) poses several mathematical and practical challenges. Frequently, in kinematic analysis, the role of the shoulder articulation is approximated to a ball-and-socket joint. Following the high-reliability computational challenge, our review challenges this inappropriate use of reductionism. Therefore, we propose that this challenge could be met by kinematic representations, that are redundant, that use an active interpretation and that emphasise on functional understanding.

An Extended Passive Motion Paradigm for Human-Like Posture and Movement Planning in Redundant Manipulators

A major challenge in robotics and computational neuroscience is relative to the posture/movement problem in presence of kinematic redundancy. We recently addressed this issue using a principled approach which, in conjunction with nonlinear inverse optimization, allowed capturing postural strategies such as Donders' law. In this work, after presenting this general model specifying it as an extension of the Passive Motion Paradigm, we show how, once fitted to capture experimental postural strategies, the model is actually able to also predict movements. More specifically, the passive motion paradigm embeds two main intrinsic components: joint damping and joint stiffness. In previous work we showed that joint stiffness is responsible for static postures and, in this sense, its parameters are regressed to fit to experimental postural strategies. Here, we show how joint damping, in particular its anisotropy, directly affects task-space movements. Rather than using damping parameters to fit a posteriori task-space motions, we make the a priori hypothesis that damping is proportional to stiffness. This remarkably allows a postural-fitted model to also capture dynamic performance such as curvature and hysteresis of task-space trajectories during wrist pointing tasks, confirming and extending previous findings in literature.

From reaching to reach-to-grasp: the arm posture difference and its implications on human motion control strategy

Reach-to-grasp arm postures differ from those in pure reaching because they are affected by grasp position/orientation, rather than simple transport to a position during a reaching motion. This paper investigates this difference via an analysis of experimental  data collected on reaching and reach-to-grasp motions. A seven-degree-of-freedom (DOFs) kinematic arm model with the swivel angle is used for the motion analysis. Compared to a widely used anatomical arm model, this model distinguishes clearly the four grasping-relevant DOFs (GR-DOFs) that are affected by positions and orientations of the objects to be grasped. These four GR-DOFs include the swivel angle that measures the elbow rotation about the shoulder-wrist axis, and three wrist joint angles. For each GR-DOF, we quantify position vs orientation task-relevance bias that measures how much the DOF is affected by the grasping position vs orientation. The swivel angle and forearm supination have similar bias, and the analysis of their motion suggests two hypotheses regarding the synergistic coordination of the macro- and micro-structures of the human arm (1) DOFs with similar task-relevance are synergistically coordinated; and (2) such synergy breaks when a task-relevant DOF is close to its joint limit without necessarily reaching the limit. This study provides a motion analysis method to reduce the control complexity for reach-to-grasp tasks, and suggests using dynamic coupling to coordinate the hand and arm of upper-limb exoskeletons.