Online collision and occlusion detection based on 3D Cuboid Maps for a daily assistive robot with a tilting LRF

This paper describes about online collision and occlusion detection for a daily assistive robot. It is assumed that 3D map about around environment is constructed by collecting datasets gradually measured using a Laser RangeFinder mounted on a tilting platform, we develop an approach to detect collision and occlusion based on the 3D map while a robot tries to manipulate objects in daily environment. As the map representation, Time-series Composite Cuboid Map is proposed. It copes with temporal sequence explicitly, and map updating is efficiently performed. Several experiments on the assumption of daily assistance by a robot, we show the effectiveness of our approach.