]> 2026-07-06T11:57:56+00:00 Optimization-Based Navigation for the DARPA Grand Challenge 0 en This research addresses the path planning problem with a nonlinear optimization method running in real time. An optimization problem is continually solved to find a time-optimal, dynamically feasible trajectory from the vehicleâs position to some receding horizon ahead (20m-70m forward). The locally optimal numerical solver optimizes both the spatial and temporal components of the trajectory simultaneously, and feeds its output to a trajectory-following controller. The method has been implemented and tested on a modified Ford E350 van. Using one stereo pair and four LADAR units as terrain sensors, the vehicle was able to consistently traverse a 2 mile obstacle course at the DGC qualifying event. At the main DGC event, the vehicle drove 8 autonomous miles through the Nevada desert before experiencing non-planning issues. During this time, the planning system generated a plan 4.28 times per second on average. This execution speed, coupled with a feedback-based trajectory-following controller was shown to be adequate at providing smooth and reliable obstacle avoidance even on complicated terrain. Dmitriy Kogan and Richard M. Murray 2006k Submitted, 2006 Conference on Decision and Control km06-cdc Conference Paper 2016-05-15T06:17:35Z 2457523.7622107 Optimization-Based Navigation for the DARPA Grand Challenge Title 102 en Title