Minimum control effort–based path planning and nonlinear guidance for autonomous mobile robots
Abstract
This article puts forth a framework using model-based techniques for path planning and guidance for an autonomous mobile robot in a constrained environment. The path plan is synthesized using a numerical navigation function algorithm that will form its potential contour levels based on the “minimum control effort.” Then, an improved nonlinear model predictive control approach is employed to generate high-level guidance commands for the mobile robot to track a trajectory fitted along the planned path leading to the goal. A backstepping-like nonlinear guidance law is also implemented for comparison with the NMPC formulation. Finally, the performance of the resulting framework using both nonlinear guidance techniques is verified in simulation where the environment is constrained by the presence of static obstacles.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Nov 01, 2018
- Source ID
- 10.1177/1729881418812635
Entities
People
- Kamesh Subbarao
- Paul Quillen
Organizations
- Air Force Research Laboratory
- University of Texas at Arlington