Motion Planning With Gamma-Harmonic Potential Fields

Abstract

This paper extends the capabilities of the harmonic potential field (HPF) approach to planning. The extension covers the situation where the workspace of a robot cannot be segmented into geometrical subregions where each region has an attribute of its own. The suggested approach uses a task-centered, probabilistic descriptor of the workspace as an input to the planner. This descriptor is processed, along with a goal point, to yield the navigation policy needed to steer the agent from any point in its workspace to the target. The approach is easily adaptable to planning in a cluttered environment containing a vector drift field. The extension of the HPF approach is based on the physical analogy with an electric current flowing in a nonhomogeneous conducting medium. The resulting potential field is known as the gamma-harmonic potential (GHPF). Proofs of the ability of the modified approach to avoid zero-probability (definite threat) regions and to converge to the goal are provided. The capabilities of the planer are demonstrated using simulation.

References in corpus (2)

• Decentralized, Self-organizing, Potential field-based Control for Individuallymotivated, Mobile Agents in a Cluttered Environment: A Vector-Harmonic Potential Field Approach
• A Hybrid, PDE-ODE Control Strategy for Intercepting an Intelligent, well-informed Target in a Stationary, Cluttered Environment

Cited by in corpus (2)

• A Harmonic Potential Field Approach for Joint Planning & Control of a Rigid, Separable Nonholonomic, Mobile Robot
• Sensor-based, time-critical mobility of autonomous robots in cluttered spaces: a harmonic potential approach