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Robotics

Master's Theses

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Decentralized, Noncooperative Multirobot Path Planning With Sample-Basedplanners, William Le Mar 2020

Decentralized, Noncooperative Multirobot Path Planning With Sample-Basedplanners, William Le

Master's Theses

In this thesis, the viability of decentralized, noncooperative multi-robot path planning algorithms is tested. Three algorithms based on the Batch Informed Trees (BIT*) algorithm are presented. The first of these algorithms combines Optimal Reciprocal Collision Avoidance (ORCA) with BIT*. The second of these algorithms uses BIT* to create a path which the robots then follow using an artificial potential field (APF) method. The final algorithm is a version of BIT* that supports replanning. While none of these algorithms take advantage of sharing information between the robots, the algorithms are able to guide the robots to their desired goals, with the …


Involuntary Signal-Based Grounding Of Civilian Unmanned Aerial Systems (Uas) In Civilian Airspace, Keith Conley Dec 2019

Involuntary Signal-Based Grounding Of Civilian Unmanned Aerial Systems (Uas) In Civilian Airspace, Keith Conley

Master's Theses

This thesis investigates the involuntary signal-based grounding of civilian unmanned aerial systems (UAS) in unauthorized air spaces. The technique proposed here will forcibly land unauthorized UAS in a given area in such a way that the UAS will not be harmed, and the pilot cannot stop the landing. The technique will not involuntarily ground authorized drones which will be determined prior to the landing. Unauthorized airspaces include military bases, university campuses, areas affected by a natural disaster, and stadiums for public events. This thesis proposes an early prototype of a hardware-based signal based involuntary grounding technique to handle the problem …


Multiple Robot Boundary Tracking With Phase And Workload Balancing, Michael Jay Boardman Jun 2010

Multiple Robot Boundary Tracking With Phase And Workload Balancing, Michael Jay Boardman

Master's Theses

This thesis discusses the use of a cooperative multiple robot system as applied to distributed tracking and sampling of a boundary edge. Within this system the boundary edge is partitioned into subsegments, each allocated to a particular robot such that workload is balanced across the robots. Also, to minimize the time between sampling local areas of the boundary edge, it is desirable to minimize the difference between each robot’s progression (i.e. phase) along its allocated sub segment of the edge. The paper introduces a new distributed controller that handles both workload and phase balancing. Simulation results are used to illustrate …