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1	Error Detection and Recovery for Robot Motion Planning with Uncertainty Donald, Bruce Randall 01 July 1987 (has links) Robots must plan and execute tasks in the presence of uncertainty. Uncertainty arises from sensing errors, control errors, and uncertainty in the geometry of the environment. The last, which is called model error, has received little previous attention. We present a framework for computing motion strategies that are guaranteed to succeed in the presence of all three kinds of uncertainty. The motion strategies comprise sensor-based gross motions, compliant motions, and simple pushing motions. robotics motion planning uncertainty error detection andsrecovery computational geometry geometric reasoning planning withsuncertainty model error EDR failure mode analysis