Active Stereo Vision for Precise Autonomous Vehicle Hitching
This thesis describes the development of a low-cost, low-power, accurate sensor designed for precise, feedback control of an autonomous vehicle to a hitch. Few studies have been completed on the hitching problem, yet it is an important challenge to be solved for vehicles in the agricultural and transportation industries. Existing sensor solutions are high cost, high power, and require modification to the hitch in order to work. Other potential sensor solutions such as LiDAR and Digital Fringe Projection suffer from these same fundamental problems.
The solution that has been developed uses an active stereo vision system, combining classical stereo vision with a laser speckle projection system, which solves the correspondence problem experienced by classic stereo vision sensors. A third camera is added to the sensor for texture mapping. As a whole, the system cost is $188, with a power usage of 2.3 W.
To test the system, a model test of the hitching problem was developed using an RC car and a target to represent a hitch. In the application, both the stereo system and the texture camera are used for measurement of the hitch, and a control system is implemented to precisely control the vehicle to the hitch. The system can successfully control the vehicle from within 35⁰ of perpendicular to the hitch, to a final position with an overall standard deviation of 3.0 mm of lateral error and 1.5⁰ of angular error. Ultimately, this is believed to be the first low power, low cost hitching system that does not require modification of the hitch in order to sense it.
- Master of Science
- Mechanical Engineering
- West Lafayette