Computational Vision for Automatic Tracking and Objective Estimation of Mobile Robot Trajectory

Sangho Park^1,

¹Department of Computer, Electronics and Graphics Technology, Central Connecticut State University, USA

Cite this paper:
Sangho Park. Computational Vision for Automatic Tracking and Objective Estimation of Mobile Robot Trajectory. Journal of Computer Sciences and Applications. 2018; 6(1):17-22. doi: 10.12691/jcsa-6-1-2

Abstract

Automatic tracking and evaluation of moving-object trajectories is critical in many applications such as performance estimation of mobile robot navigation. Mobile robot is an effective platform for stimulating student motivation at K-12 institutions as well as a good tool for rigorous engineering practices in colleges, universities, and graduate schools. Developing new mobile robot platforms and algorithms requires objective estimation of navigation performance in a quantitative manner. Conventional methods to estimate mobile robot navigation typically rely on manual usage of chronometer to measure the time spent for the completion of a given task or counting the success rate on the task. This paper proposes an alternative; a multi-camera vision system that can automatically track the movement of mobile robot and estimate it in terms of physics-based profiles: position, velocity, and acceleration of the robot in the trajectory with respect to a user-defined world-coordinate system. The proposed vision system runs two synchronized cameras to simultaneously capture and track the movement of the robot at 30 frames per second. The system runs a homography-based projection algorithm that converts the view-dependent appearance of the robot in the camera images to a view-independent orthographic projection mapped on the registered world coordinate system. This enables the human evaluator to view and estimate the robot navigation from a virtual top-down view embedded with the physics-based profiles regardless of the actual cameras’ viewing positions. The proposed system can also be used for other domains including highway traffic monitoring and intelligent video surveillance.

Keywords:
computational vision object tracking trajectory estimation robot navigation multiple view geometry

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