Modeling and Control for Vision Based Rear Wheel Drive Robot and Solving Indoor SLAM Problem Using LIDAR

Abstract

abstract: To achieve the ambitious long-term goal of a feet of cooperating Flexible Autonomous Machines operating in an uncertain Environment (FAME), this thesis addresses several critical modeling, design, control objectives for rear-wheel drive ground vehicles. Toward this ambitious goal, several critical objectives are addressed. One central objective of the thesis was to show how to build low-cost multi-capability robot platform that can be used for conducting FAME research. A TFC-KIT car chassis was augmented to provide a suite of substantive capabilities. The augmented vehicle (FreeSLAM Robot) costs less than $500 but offers the capability of commercially available vehicles costing over$2000. All demonstrations presented involve rear-wheel drive FreeSLAM robot. The following summarizes the key hardware demonstrations presented and analyzed: (1)Cruise (v, ) control along a line, (2) Cruise (v, ) control along a curve, (3) Planar (x, y) Cartesian Stabilization for rear wheel drive vehicle, (4) Finish the track with camera pan tilt structure in minimum time, (5) Finish the track without camera pan tilt structure in minimum time, (6) Vision based tracking performance with different cruise speed vx, (7) Vision based tracking performance with different camera fixed look-ahead distance L, (8) Vision based tracking performance with different delay Td from vision subsystem, (9) Manually remote controlled robot to perform indoor SLAM, (10) Autonomously line guided robot to perform indoor SLAM. For most cases, hardware data is compared with, and corroborated by, model based simulation data. In short, the thesis uses low-cost self-designed rear-wheel drive robot to demonstrate many capabilities that are critical in order to reach the longer-term FAME goal.Dissertation/ThesisDefense PresentationMasters Thesis Electrical Engineering 201