Comparing the Power of Robots

  • Authors:
  • Jason M. O'Kane;Steven M. Lavalle

  • Affiliations:
  • Department of Computer Science, University of Illinoisat Urbana-Champaign, 201 North Goodwin Avenue Urbana, IL 61801, USA;Department of Computer Science, University of Illinoisat Urbana-Champaign, 201 North Goodwin Avenue Urbana, IL 61801, USA

  • Venue:
  • International Journal of Robotics Research
  • Year:
  • 2008

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Abstract

Robots must complete their tasks in spite of unreliableactuators and limited, noisy sensing. In this paper, we considerthe information requirements of such tasks. What sensing andactuation abilities are needed to complete a given task? Are somerobot systems provably "more powerful", in terms of the tasks thatthey can complete, than others? Can we find meaningful equivalenceclasses of robot systems? This line of research is inspired by thetheory of computation, which has produced similar results forabstract computing machines. Our basic contribution is a dominancerelation over robot systems that formalizes the idea that somerobots are stronger than others. This comparison, which is based onhow the robots progress through their information spaces, induces apartial order over the set of robot systems. We prove some basicproperties of this partial order and show that it is directlyrelated to the robots' ability to complete tasks. We give examplesto demonstrate the theory, including a detailed analysis of alimited-sensing global localization problem.