A Study of the Role of Plant Properties in Arm Trajectory Formation

This paper describes the response of a neural-network model of an anthropomorphic arm to various patterns of activation of the arm muscles. The arm model was introduced and described in detail in [1]. The purpose of the simulation experiments presented here is to study the relative role of control strategies and plant properties in trajectory formation, namely which features of simple arm movements can be attributed to the properties of the plant alone { a study that might provide some guidelines for the design of arti cial arms. Our simulations demonstrate the performance of the model at steady-state, what movements the model produces in response to various activations of its muscles, and the generalization abilities of the recurrent neural network that implements the forward dynamic transformation. The results of our simulations emphasize the role of the intrinsic properties of the plant in generating movements with anthropomorphic qualities such as smoothness and unimodal velocity pro les and demonstrate that the task of an eventual controller for such an arm could be simply that of programming the amplitudes and durations of steps of neural input without considering additional motor details. Our ndings are relevant to the design of arti cial arms and, with some caveats, to the study of brain strategies in the arm motor system.