Internet Archive Scholar

Randomized searches and nonlinear programming in trajectory planning

T. Karatas, F. Bullo
Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)  

Preserved Fulltext

fulltext thumbnail
Web Archive Capture PDF (577.2 kB)
https://web.archive.org/web/20170810171131/http://motion.me.ucsb.edu/pdf/2001h-kb.pdf?origin=publication_detail

A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL. The file type is application/pdf.

This paper presents a novel trajectory planning algorithm for nonlinear dynamical systems evolving in environments with complex obstacles. The incremental search algorithm entails (i) a global exploration strategy based on randomization and on a rapidly-exploring heuristic, and (ii) a local planner based on collocation and nonlinear programming. To numerically validate the design, we consider a six degree of freedom vehicle model subject to saturation limits on the control inputs and obstacles
more » ... n the state variables. Experimental results indicate that the proposed scheme outperforms implementations based solely on nonlinear programming or on randomization.
doi:10.1109/cdc.2001.981008 fatcat:zdazqm7t6bfp5dcq5xm74n5lge
Citation

T. Karatas, F. Bullo. "Randomized searches and nonlinear programming in trajectory planning." Proceedings of the 40th IEEE Conference on Decision and Control (Cat. No.01CH37228)