Kinematic design optimization of a parallel ankle rehabilitation robot using modified genetic algorithm

Rehabilitation robotics is an evolving area of active research and recently novel mechanisms have been proposed to reinstate complex human movements. Parallel robots are of particular interest to researchers since they are rigid and can provide enough load capacity for human joint movements. This paper proposes a soft parallel robot (SPR) for ankle joint rehabilitation. Kinematic workspace analysis is carried out and the singularity criterion of the SPR's Jacobian matrix is used to define the feasible workspace. A global conditioning number (GCN) is defined using the Jacobian matrix as a performance index for the evaluation of the robot design. An optimization problem is formulated to minimize the GCN using modified genetic algorithm (GA). Results from simple GA and modified GA are compared and discussed. As a result of the optimization, an optimal robot design is obtained which has a near unity GCN with almost uniform distribution in the entire feasible workspace of the robot.