Temporal Logic Planning and Control of Robotic Swarms by Hierarchical Abstractions

• Published in: IEEE transactions on robotics Vol. 23; no. 2; pp. 320 - 330
• Main Authors: Kloetzer, M., Belta, C.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.04.2007; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Applied sciences; Artificial intelligence; Automation; Collision avoidance; Computer architecture; Computer science; control theory; systems; Containment; Control; Control system synthesis; Control systems; Control theory. Systems; Exact sciences and technology; Industrial metrology. Testing; Laws; Logic; Mathematical models; Mechanical engineering. Machine design; model checking; motion planning; Obstacles; Orbital robotics; Power engineering computing; Robot control; robotic swarms; Robotics; Robotics and automation; Robots; Shape; Systems engineering and theory; Temporal logic; Velocity control; Specification language; Control program; Temporal logic; Robotics; Hierarchized structure; Polyhedron; System with n degrees of freedom; Dimensional control; Logic control; Model checking; Natural language; Planning; Collision avoidance
• ISSN: 1552-3098; 1941-0468
• DOI: 10.1109/TRO.2006.889492

We develop a hierarchical framework for planning and control of arbitrarily large groups (swarms) of fully actuated robots with polyhedral velocity bounds moving in polygonal environments with polygonal obstacles. At the first level of hierarchy, we aggregate the high-dimensional control system of the swarm into a small-dimensional control system capturing its essential features. These features describe the position of the swarm in the world and its size. At the second level, we reduce the problem of controlling the essential features of the swarm to a model-checking problem. In the obtained hierarchical framework, high-level specifications given in natural language, such as linear temporal logic formulas over linear predicates in the essential features, are automatically mapped to provably correct robot control laws. For the particular case of an abstraction based on centroid and variance, we show that swarm cohesion, interrobot collision avoidance, and environment containment can also be specified and automatically guaranteed in our framework. The obtained communication architecture is centralized