This MQP attempts to prototype a depth camera-based vision system for the Goat Cart the Autonomous Golf Cart, with Microsoft Kinect. This vision system works by polling depth data using Microsoft Kinect and giving inputs to other modules i.e. brakes, and steering module so that the vehicle can avoid obstacles. Based on a simple occupancy grid algorithm the vision system was able to give correct inputs to other modules to avoid obstacles in a lab test where movement decision results were printed onto the console. This MQP also explores the logistics of a LIDAR-based vision for the Goat Cart.

• This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

Creator

• Islam, Muhaimin

Publisher

• Worcester Polytechnic Institute

Identifier

• 61111
• E-project-040722-131116

Advisor

• Wyglinski, Alexander

Year

• 2022

Date created

• 2022-04-07

Resource type

• Major Qualifying Project

Major

• Electrical & Computer Engineering

Rights statement

• In Copyright