Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, September, 2020 ; Cataloged from student-submitted PDF of thesis. ; Includes bibliographical references (pages 20-21). ; This contribution is an optimization-based method for robotic path-planning that is able to recover vehicle controls in addition to discovering an optimized, feasible trajectory from start to goal for vehicles with arbitrary dynamics. The motion planner extends the application of factor-graph optimization commonly used in simultaneous localization and mapping tasks to the path-planning task, specifically the "timed elastic band" trajectory optimization approach [1] for control input extraction functionality. This is achieved by the introduction of control input-dependent vertices into the factor-graph along with a way to systematically design dynamics violation costs without relying on hand-picked geometric parameters. An implementation of the planner successfully recovers vehicle control inputs and produces feasible trajectories in simulation testing. ; by Nadya L. Balabanska. ; M. Eng. ; M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
Motion planning with dynamic constraints through pose graph optimization
2020-01-01
1227274206
Hochschulschrift
Elektronische Ressource
Englisch
DDC: | 629 |
Probabilistic motion planning and optimization incorporating chance constraints
BASE | 2018
|Kinematic motion planning with regional planning constraints
Europäisches Patentamt | 2018
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