Simultaneous localization and mapping for a mobile robot
First Claim
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1. A method of localizing a mobile robot, the method comprising:
- receiving sensor data of a scene about the robot, the sensor data comprising a three-dimensional point cloud;
executing a particle filter having a set of particles, each particle having an associated variance occupancy grid map and a robot location hypothesis;
accumulating cloud points in cells of the variance occupancy grid map based on first and second coordinates of the cloud points, each cell accumulating a height variance based on a third coordinate of the accumulated cloud points;
updating the variance occupancy grid map associated with each particle based on the received sensor data;
assessing a weight for each particle based on the received sensor data;
selecting at least one particle based on its weight; and
determining a location of the robot based on the at least one selected particle.
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Abstract
A method of localizing a mobile robot includes receiving sensor data of a scene about the robot and executing a particle filter having a set of particles. Each particle has associated maps representing a robot location hypothesis. The method further includes updating the maps associated with each particle based on the received sensor data, assessing a weight for each particle based on the received sensor data, selecting a particle based on its weight, and determining a location of the robot based on the selected particle.
156 Citations
20 Claims
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1. A method of localizing a mobile robot, the method comprising:
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receiving sensor data of a scene about the robot, the sensor data comprising a three-dimensional point cloud; executing a particle filter having a set of particles, each particle having an associated variance occupancy grid map and a robot location hypothesis; accumulating cloud points in cells of the variance occupancy grid map based on first and second coordinates of the cloud points, each cell accumulating a height variance based on a third coordinate of the accumulated cloud points; updating the variance occupancy grid map associated with each particle based on the received sensor data; assessing a weight for each particle based on the received sensor data; selecting at least one particle based on its weight; and determining a location of the robot based on the at least one selected particle. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20)
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Specification