A rescue robot using imu data fusion to estimate 3D pose

Abstract

The invention discloses a rescue robot that uses IMU data fusion to estimate a three-dimensional pose. The robot includes a mobile platform on which an image acquisition module, a distance information acquisition module, a data processing module, a motion control module and a remote control module are mounted. module, wherein: the image acquisition module is used to collect image information in the environment where the robot is located to search for the person to be rescued; the distance information acquisition module is used to obtain IMU data through the inertial measurement unit, and obtain laser points through the laser radar Cloud data; the remote control module is used to receive the control instruction sent by the industrial computer; the motion control module is used to generate the current environmental map, and the position of the person to be rescued is marked on the environmental map; according to the The control instructions enable the robot to reach the target point through path planning and obstacle avoidance algorithms; the data processing module is used to fuse the IMU data and laser point cloud data to estimate the three-dimensional pose of the robot.

Description

technical field [0001] The invention relates to the field of robots and mapping, in particular to a rescue robot that uses inertial measurement (Inertial measurement unit, IMU) data fusion to estimate a three-dimensional pose. Background technique [0002] The autonomous mobile robot's estimation of its own pose and perception and modeling of the surrounding environment, that is, Simultaneous Localization And Mapping, is the most important ability for a mobile robot to truly operate autonomously in an unknown environment in the real world. one. Because lidar has very accurate ranging performance and strong anti-interference ability, the mapping method based on lidar has attracted great attention of engineers. Many navigation systems based on occupancy grid maps, such as the open source algorithm GMapping, Hector mapping and Cartographer, have been applied to indoor robot navigation and perform well in indoor environments. [0003] The lidar-based mapping algorithm can accu...

AI Technical Summary

Problems solved by technology

[0004] Although the mapping algorithm based on 3D point cloud information can provide robot 3D pose estimation and environmental maps, it requires multi-line lidar sensors to provide information

Multi-line lidar is expensive and bulky, which is not conducive to the low cost and miniaturization of small rescue robots, and this type of algorithm has a large amount of calculation and is very sensitive to parameter settings

Although the cost of vision-based mapping algorithms is low, the robustness of such algorithms needs to be improved, and there is also the problem of large amount of calculation.

Similar to the uneven environment of the rescue environment, the lidar cannot collect the three-dimensional height information of the robot, making it difficult for the robot to independently explore in the complex environment

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