This paper presents a robust target tracking algorithm for a mobile sensor with a fan-shaped field of view and finite sensing range. The goal of the mobile robot is to track a moving target such that the probability of losing the target is minimized. We assume that the distribution of the next position of a moving target can be estimated using a motion prediction algorithm. If the next position of a moving target has the Gaussian distribution, the proposed algorithm can guarantee the tracking success probability. In addition, the proposed method minimizes the moving distance of the mobile robot based on a bound on the tracking success probability. While the problem considered in this paper is a non-convex optimization problem, we derive analytical solutions which can be easily solved in real-time. The performance of the proposed method is evaluated extensively in simulation and validated in pedestrian following experiments using a Pioneer mobile robot with a Microsoft Kinect sensor.
|Number of pages||6|
|Journal||Proceedings - IEEE International Conference on Robotics and Automation|
|Publication status||Published - 2015 Jun 29|
|Event||2015 IEEE International Conference on Robotics and Automation, ICRA 2015 - Seattle, United States|
Duration: 2015 May 26 → 2015 May 30
Bibliographical notePublisher Copyright:
© 2015 IEEE.
ASJC Scopus subject areas
- Control and Systems Engineering
- Artificial Intelligence
- Electrical and Electronic Engineering