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Monte Carlo localization (MCL) is a sample-based approach for representing probability density for the pose of a robot. MCL is widely used for mobile robots because of its robustness with respect to sensor noise. On the other hand, MCL can fail to estimate a pose of a robot if objects block measuring range of a laser sensor of the robot. Even though MCL fails to estimate the pose of the robot, MCL...
This paper describes methods of environment map representation and plane detection for daily assistive robots. Under the assumption that 3D information of around environment is constructed by collecting range data gradually measured, we propose an effective map representation named TCCM (Time-series Composite Cuboid Map). The method copes with temporal sequence explicitly, and map updating is efficiently...
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...
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