A Target Person Locating Framework Based on Distributed Odometries

Lei Pang, Zhiqiang Cao, Junzhi Yu, Zhonghui Li, Lei Zhao, Pei Lv

Abstract: The ability to follow a specified target person by a mobile robot plays an important role. The continuity of person following is a key factor to the performance and practicability. In the practical person following, the failure easily occurs when the target person is out of the sensing range of the robot, which destroys the continuity of the person following and still remains a challenge. To solve the problem of following recovery, a locating framework based on distributed odometries is proposed, which can locate the target effectively with a robot-end odometry and a target-end odometry. In this framework, the robot-end odometry and the target-end odometry are used to estimate poses of the robot and positions of the target person, respectively. These two odometries are fused with the combination of locations of the target person in the robot coordinate system. On this basis, the robot can obtain the estimated target location by receiving the position information from the target-end odometry with a wireless network, which is then transformed to the coordinate in the robot-end odometry. When a missing case occurs, the mobile robot can continue to retrieve the target person by moving along the sampling transformed positions. An implement with the robot-end LiDAR odometry and target-end wearable visual-inertial odometry is given to evaluate the proposed locating framework. Experiments reveal that a mobile robot can recover the normal person following even if the target person is far away from the robot.