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Symbolic Control and Planning of Robotic Motion [Grand Challenges of Robotics]
Departmental Papers (ESE)
  • Calin Belta, Boston University
  • Antonio Bicci, University of Pisa
  • Magnus Egerstedt, Georgia Institute of Technology
  • Emilio Frazzoli, Massachusetts Institute of Technology
  • Eric Klavins, University of Washington
  • George J Pappas, University of Pennsylvania
Document Type
Journal Article
Date of this Version
Copyright 2007 IEEE. Reprinted from IEEE Robotics and Automation, Volume 14, Issue 1, March 2007, pages 51-70.

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Mobile robots are complex systems that combine mechanical elements such as wheels and gears, electromechanical devices such as motors, clutches and brakes, digital circuits such as processors and smart sensors, and software programs such as embedded controllers. They have mechanical constraints (e.g., a car-like robot cannot move sideways), limited energy resources, and computation, sensing, and communication capabilities. They operate in environments cluttered with possibly moving and shape changing obstacles, and their objectives can change over time, such as in the case of appearing and disappearing targets. Robot motion planning and control is the problem of automatic construction of robot control strategies from task specifications given in high-level, human-like language. The challenge in this area is the development of computationally efficient frameworks allowing for systematic, provably correct, control design accommodating both the robot constraints and the complexity of the environment, while at the same time allowing for expressive task specifications.

Citation Information
Calin Belta, Antonio Bicci, Magnus Egerstedt, Emilio Frazzoli, et al.. "Symbolic Control and Planning of Robotic Motion [Grand Challenges of Robotics]" (2007)
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