The reliable recovery mechanism for person-following robot in case of missing target - Minh Do Hoang; Choi, Jong-Suk; Yun, Sang-Seok (2017 14TH INTERNATIONAL CONFERENCE ON UBIQUITOUS ROBOTS AND AMBIENT INTELLIGENCE (URAI), 2017)
This paper proposed a reliable recovery mechanism for person-following robot in case of missing target. The prior information such as previous human positons (before losing point) is used in order to predict the unexpected human positions by probabilistic approach (using Kalman Filter). In addition, map information is also utilized which allows robot to grasp searching route in order to redetect human target. Map also assists the robot in navigating smoothly with obstacle avoidance function to reach the human target. The experimental results demonstrate the outperfounance of proposed recovery mechanism.