Performance Analysis of Constant Speed Local Abstacle Avoidance Controller Using a MPC Algorithym on Granular Terrain Nicholas Haraus Marquette University
Marquette University e-Publications@Marquette Master's Theses (2009 -) Dissertations, Theses, and Professional Projects Performance Analysis of Constant Speed Local Abstacle Avoidance Controller Using a MPC Algorithym on Granular Terrain Nicholas Haraus Marquette University Recommended Citation Haraus, Nicholas, "Performance Analysis of Constant Speed Local Abstacle Avoidance Controller Using a MPC Algorithym on Granular Terrain" (2017). Master's Theses (2009 -). 443. http://epublications.marquette.edu/theses_open/443 PERFORMANCE ANALYSIS OF A CONSTANT SPEED LOCAL OBSTACLE AVOIDANCE CONTROLLER USING A MPC ALGORITHM ON GRANULAR TERRAIN by Nicholas Haraus, B.S.M.E. A Thesis submitted to the Faculty of the Graduate School, Marquette University, in Partial Fulfillment of the Requirements for the Degree of Master of Science Milwaukee, Wisconsin December 2017 ABSTRACT PERFORMANCE ANALYSIS OF A CONSTANT SPEED LOCAL OBSTACLE AVOIDANCE CONTROLLER USING A MPC ALGORITHM ON GRANULAR TERRAIN Nicholas Haraus, B.S.M.E. Marquette University, 2017 A Model Predictive Control (MPC) LIDAR-based constant speed local obstacle avoidance algorithm has been implemented on rigid terrain and granular terrain in Chrono to examine the robustness of this control method. Provided LIDAR data as well as a target location, a vehicle can route itself around obstacles as it encounters them and arrive at an end goal via an optimal route. This research is one important step towards eventual implementation of autonomous vehicles capable of navigating on all terrains. Using Chrono, a multibody physics API, this controller has been tested on a complex multibody physics HMMWV model representing the plant in this study. A penalty-based DEM approach is used to model contacts on both rigid ground and granular terrain.
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