Integrated motion planning and model learning for mobile robots with application to marine vehicles

Robust motion planning algorithms for mobile robots consider stochasticity in the dynamic model of the vehicle and the environment. A practical robust planning approach balances the duration of the motion plan with the probability of colliding with obstacles. This thesis develops fast analytic algorithms for predicting the collision probability due to model uncertainty and random disturbances in the environment for a planar holonomic vehicle such as a marine surface vessel. These predictions lead to a robust motion planning algorithm that nds the optimal motion plan quickly and efficiently. By incorporating model learning into the predictions, the integrated algorithm exhibits emergent active learning strategies to autonomously acquire the model data needed to safely and eectively complete the mission. The motion planner constructs plans through a known environment by concatenating maneuvers based upon speed controller setpoints. A model-based feedforward/ feedback controller is used to track the resulting reference trajectory, and the model parameters are learned online with a least squares regression algorithm. The path-following performance of the vehicle depends on the effects of unknown environmental disturbances and modeling error. The convergence rate of the parameter estimates depends on the motion plan, as different plans excite different modes of the system.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Mechanical Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2009

Author dc:creator

• Greytak, Matthew B. (Matthew Bardeen)

Advisor dc:contributor.advisor

• Franz S. Hover.

• Mechanical Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/54874

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/54874