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Date of Award


Document Type

Campus Access Master's Report

Degree Name

Master of Science in Electrical and Computer Engineering (MS)

Administrative Home Department

Department of Electrical and Computer Engineering

Advisor 1

Jung Yun Bae

Advisor 2

John Pakkala

Committee Member 1

Myoungkuk Park

Committee Member 2

Nathir Rawashdeh


Path planning forms the fundamental requirement to facilitate autonomous navigation in Autonomous Vehicles (AVs). Ensuring a cost-efficient, safe, and collision-free path has been the primary objective of most research concerned with path planning. Path planning is accomplished at two levels: global and local. While global path planning can provide reasonable obstacle avoidance in static environments, local path planning or reactive control is better suited to dynamic and fast-changing environments. Integration of the two techniques is also employed to account for either's shortcomings and, hence, enhance the collision avoidance capability and optimal trajectory generation. However, in complex scenarios like constricted spaces or close encounters between agents, even the integrated approaches fail, resulting in a collision or a deadlock. Hence, it necessitates employing cooperative collision avoidance techniques to address these issues and ensure successful, collision-free navigation for AVs.

This research's primary objective is to explore a potential solution to enable a cooperative collision avoidance mechanism for autonomous navigation of wheeled mobile robots in a constricted multi-robot environment. This work presents an overview of the current path planners and discusses their limitations. This work studies and explores the capabilities of employing the classic Elastic Band Methods(EBM) path planning technique and Model Predictive Control(MPC) trajectory optimization technique in conjunction to explore the possible cooperative collision avoidance capabilities. Integrating the two and extending the approach to 3D environments forms the basis for our future work.