Guaranteed Avoidance of Unpredictable, Dynamically Constrained Obstacles using Velocity Obstacle Sets

Abstract

Dynamic obstacle avoidance is an important, ubiquitous, and often challenging problem for autonomous mobile robots. This thesis presents a new method to guarantee collision avoidance with respect to moving obstacles that have constrained dynamics but move unpredictably. Velocity Obstacles have been widely used to plan trajectories that avoid collisions with obstacles under the assumption that the path of the objects are either known or can be accurately predicted ahead of time. However, for real systems, this predicted path will typically only be accurate over short time-horizons. To achieve safety over longer time periods, the method introduced here instead considers the set of all reachable points by an obstacle assuming that the dynamics the unicycle model, which has known constant forward speed and a maximum turn rate (sometimes called the Dubins car model).

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2011
Accession Number
ADA546515

Entities

People

  • Albert Wu

Organizations

  • Massachusetts Institute of Technology

Tags

DTIC Thesaurus Topics

  • Aeronautics
  • Algorithms
  • Astronautics
  • Boundaries
  • Collision Avoidance
  • Collisions
  • Computational Complexity
  • Dynamics
  • Environment
  • Guarantees
  • Motion Planning
  • Navigation
  • Simulations
  • Simulators
  • Standards
  • Time Intervals
  • Trajectories

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Autonomy