Abstract
The generation of goal-directed movements requires the solution of many difficult computational problems. Among these are transformations from extrinsic to intrinsic reference frames, specifying solution paths, removing under-specification due to excess degrees of freedom and path multiplicity, constraint satisfaction, and error correction. There are no current motor-control computational models that address these issues in the context of realistic arm movement with redundant degrees of freedom. In this paper, we conjecture there is a geometric stage between sensory input and physical execution. The geometric stage determines movement trajectories independently of forces. It uses a gradient technique that relies on the metric of the space of postures to resolve endpoint path selection, posture-change specification, error correction, and multiple constraint satisfaction on-line without preplanning. The model is instantiated in an arm with seven degrees of freedom that moves in three-dimensional space. Simulated orientation-matching movements are compared with actual human movement data to assess the validity of several of the model's behavioral predictions.
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