Occupancy Voxel Metric Based Iterative Closest Point for Position Tracking in 3D Environments
Many applications for robotics require that the robot know its current position in the environment. While there exist several solutions for localizing a robot, even in a previously unknown environment, they often require an estimate of the robot’s motion. However, in many situations, a robot may not have motion encoders, or its encoders may be highly inaccurate. We have developed an algorithm for tracking the position of a robot, based on a rangefinder device, that is robust to temporary errors in the range scan. By aligning each scan to an occupancy grid of prior scan data, we can find the robot’s position more accurately than current techniques which only align to the previous scan. In addition, our solution can track the position of the robot based on three dimensional scan data, instead of requiring that the range sensor be fixed in a level plane.
Adam Milstein Matthew McGill Timothy Wiley Rudino Salleh Claude Sammut
University of New South Wales
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
4048-4053
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）