Task-based decision making and control of robotic manipulators

Abstract

Redundancy affords an opportunity to deploy robotic manipulators in a broader variety of tasks owing to extra system resources.Decision making is a procedure that manages these extra resources and utilizes them in a meaningful fashion.Decision making is inherently complex and this complexity is a major hindrance to wider acceptance of redundant manipulators in various robotic applications.This report aims directly at decreasing this complexity by incorporating the concept of task requirements as an integral part of the decision making process.Most traditional Redundancy Resolution Techniques (RRTs) place an undue burden on the user by forcing him to choose a set of performance criteria and assign relative importance to each criterion for a given task.The Task-Based Redundancy Resolution (TBRR) approach presented here changes all that by directly utilizing robotic task requirements in terms of speed, force, and accuracy in