Show simple item record

dc.contributor.advisorEgerstedt, Magnus
dc.contributor.authorDroge, Greg Nathanael
dc.date.accessioned2014-05-22T15:30:21Z
dc.date.available2014-05-22T15:30:21Z
dc.date.created2014-05
dc.date.issued2014-04-01
dc.date.submittedMay 2014
dc.identifier.urihttp://hdl.handle.net/1853/51864
dc.description.abstractWe present a motion control framework which allows a group of robots to work together to decide upon their motions by minimizing a collective cost without any central computing component or any one agent performing a large portion of the computation. When developing distributed control algorithms, care must be taken to respect the limited computational capacity of each agent as well as respect the information and communication constraints of the network. To address these issues, we develop a distributed, behavior-based model predictive control (MPC) framework which alleviates the computational difficulties present in many distributed MPC frameworks, while respecting the communication and information constraints of the network. In developing the multi-agent control framework, we make three contributions. First, we develop a distributed optimization technique which respects the dynamic communication restraints of the network, converges to a collective minimum of the cost, and has transients suitable for robot motion control. Second, we develop a behavior-based MPC framework to control the motion of a single-agent and apply the framework to robot navigation. The third contribution is to combine the concepts of distributed optimization and behavior-based MPC to develop the mentioned multi-agent behavior-based MPC algorithm suitable for multi-robot motion control.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subjectModel predictive control
dc.subjectDistributed optimization
dc.subjectNetworked-control
dc.subjectMulti-agent control
dc.subject.lcshAutomatic control
dc.subject.lcshPredictive control
dc.subject.lcshMultiagent systems
dc.subject.lcshAlgorithms
dc.titleBehavior-based model predictive control for networked multi-agent systems
dc.typeDissertation
dc.description.degreePh.D.
dc.contributor.departmentElectrical and Computer Engineering
thesis.degree.levelDoctoral
dc.contributor.committeeMemberShamma, Jeff
dc.contributor.committeeMemberTaylor, David
dc.contributor.committeeMemberWardi, Yorai
dc.contributor.committeeMemberKemp, Charles
dc.date.updated2014-05-22T15:30:21Z


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record