A Cell Decomposition Approach to Robotic Trajectory Planning via Disjunctive Programming

Loading...
Thumbnail Image

Date

2012

Authors

Swingler, Ashleigh

Advisors

Ferrari, Silvia

Journal Title

Journal ISSN

Volume Title

Repository Usage Stats

590
views
2878
downloads

Abstract

This thesis develops a novel solution method for the problem of collision-free, optimal control of a robotic vehicle in an obstacle populated environment. The technique presented combines the well established approximate cell decomposition methodology with disjunctive programming in order to address both geometric and kinematic trajectory concerns. In this work, an algorithm for determining the shortest distance, collision-free path of a robot with unicycle kinematics is developed. In addition, the research defines a technique to discretize nonholonomic vehicle kinematics into a set of mixed integer linear constraints. Results obtained using the Tomlab/CPLEX mixed integer quadratic programming software exhibit that the method developed provides a powerful initial step in reconciling geometric path planning methods with optimal control techniques.

Description

Provenance

Citation

Citation

Swingler, Ashleigh (2012). A Cell Decomposition Approach to Robotic Trajectory Planning via Disjunctive Programming. Master's thesis, Duke University. Retrieved from https://hdl.handle.net/10161/5542.

Collections


Dukes student scholarship is made available to the public using a Creative Commons Attribution / Non-commercial / No derivative (CC-BY-NC-ND) license.