Languages, Behaviors, Hybrid Architectures and Motion Control

Abstract

In this paper, the authors put forth a framework that integrates features of reactive planning models with modern control-theory-based approaches to motion control of robots. They introduce a motion description language, MDLe, that provides a formal basis for robot programming using behaviors, and at the same time permits incorporation of kinematic and dynamic models of robots given in the form of differential equations. In particular, behaviors for robots are formalized in terms of kinetic state machines, a motion description language, and the interaction of the kinetic state machine with real-time information from (limited range) sensors. This formalization allows them to create a mathematical basis for the study of such systems, including techniques for integrating sets of behaviors. In addition, they suggest optimality criteria for comparing both atomic and compound behaviors in various environments. They demonstrate the use of MDLe in the area of motion planning for nonholonomic robots. Such models impose limitations on stabilization via smooth feedback. Piecing together open loop and closed loop trajectories becomes essential in these circumstances, and MDLe enables one to describe such piecing together in a systematic manner. A reactive planner using the formalism of the paper is described. The authors also demonstrate obstacle avoidance with limited range sensors as a test of this planner.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1997
Accession Number
ADA453760

Entities

People

  • James Hendler
  • P.S.Krishnaprasad
  • Vikram Manikonda

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Abstracts
  • Collision Avoidance
  • Computer Science
  • Control Theory
  • Differential Equations
  • Electrical Engineering
  • Engineering
  • Information Operations
  • Language
  • Military Research
  • Motion Planning
  • Robots
  • Universities

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Control Systems Engineering.
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Autonomous System Control