Undergrad Research Project - Path Planning Parking Algorithms for Self-Driving Trailer Trucks

Fall 2016

Edward Ahn
Raj Rajkumar
Project description

This project will build a set of path planning parking algorithms for self-driving trailer trucks. Parking maneuvers for trailer trucks with physical constraints at loading docks can be challenging even for experienced human drivers. In contrast, while self-driving trucks can lead to better safety on both local roads and highways, these trucks must also able to park themselves in tight spots using accurate modeling of vehicle dynamics, kinematics and motion paths. This project will utilize the Gazebo 3-D graphics engine on ROS (Robot Operating System), and implement a realistic 3-D simulation environment where trailer trucks can successfully complete different kinds of parking maneuvers. This will result in a successful virtual simulation of trailer trucks parking themselves. A successful completion of this effort will lay the foundations for a follow-on project later that will implement these algorithms on a physical but scale-model of a trailer truck.

Flexible Deliverable Deadlines September 16 - Set up ROS September 23 - Set up Gazebo October 7 - Get a truck model working in Gazebo October 28 - Be able to simulate movement of a truck, incorporating truck dynamics and kinematic models December 9 - Complete simulation of different parking maneuvers, such as tail-in, head-in, parallel parking and loading dock parking in constrained environments

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