PERCEPTION
uSLAM Implementation for Autonomous Underground Robot
Elisabeth Menéndez, Santiago Martínez de la Casa, Marcos Fernández Marín, Carlos Balaguer
- 发表年份
- 2019
- 引用次数
- 8
摘要
This paper presents an Underground Simultaneous Localization and Mapping (uSLAM) method to localize an autonomous underground robotic system and map its surroundings. A Rao-Blackwellized Particle Filter (RBPF) with the information provided by a Ground Penetrating Radar (GPR) system installed in the robot and odometry data is described. RBPF generates possible trajectories, where each one of them has its 3D occupancy grid map. A scan matching method based on groups of GPR measurements to improve the proposed trajectories is also described.
关键词
Occupancy grid mappingOdometryGround-penetrating radarComputer visionParticle filterComputer scienceArtificial intelligenceRobotMobile robotUnmanned ground vehicle
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