Search for: All records

This paper presents an online, robust, and model-free motion planning framework for kinodynamic systems. In particular, we employ a Q-learning algorithm for a two player zero-sum dynamic game to account for worst-case disturbances and kinodynamic constraints. We use one critic, and two actor approximators to solve online the finite horizon minimax problem with a form of integral reinforcement learning. We then leverage a terminal state evaluation structure to facilitate the online implementation. A static obstacle augmentation, and a local replanning framework is presented to guarantee safe kinodynamic motion planning. Rigorous Lyapunov-based proofs are provided to guarantee closed-loop stability, while maintaining robustness and optimality. We finally evaluate the efficacy of the proposed framework with simulations and we provide a qualitative comparison of kinodynamic motion planning techniques 

This paper presents a compliant, underactuated finger for the development of anthropomorphic robotic and prosthetic hands. The finger achieves both flexion/extension and adduction/abduction on the metacarpophalangeal joint, by using two actuators. The design employs moment arm pulleys to drive the tendon laterally and amplify the abduction motion, while also maintaining the flexion motion. Particular emphasis has been given to the analysis of the mechanism. The proposed finger has been fabricated with the hybrid deposition manufacturing technique and the actuation mechanism's efficiency has been validated with experiments that include the computation of the reachable workspace, the assessment of the exerted forces at the fingertip, the demonstration of the feasible motions, and the presentation of the grasping and manipulation capabilities. The proposed mechanism facilitates the collaboration of the two actuators to increase the exerted finger forces. Moreover, the extended workspace allows the execution of dexterous manipulation tasks.