Adaptive Feedforward Control Applied to Robotics

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The goal of this research is to explore how robots might follow a trajectory more accurately with practice of that trajectory. The research focuses on an adaptive feedforward control, where a feedforward command is modified on the basis of previous performance errors. Proposed trajectory learning algorithms will be analyzed mathematically, evaluated through simulation, and implemented on the MIT Serial Link Direct Drive Robot Arm. The objective of this research is to make robots, and machines in general, move more accurately. This research will lead to improved robot performance, and the ideas and algorithms developed can be applied directly to the control of a wide variety of machines. Robots and other machines will be able to move more accurately at higher speeds, allowing faster throughput and greater productivity. In addition, more accurate performance will make it easier to program robots to do particular tasks, as programmers will no longer have to anticipate and compensate for dynamic errors.