3 accepted papers
Obstacle avoidance is a significant part of robot autonomous navigation. Compared with traditional legged and actively driven wheeled robots, the skiing robot is a nonholonomic system, which cannot precisely control the speed. This paper presents an obstacle avoidance method based on the risk region
This letter presents SW-LIO, a tightly coupled LiDAR-inertial odometry based on the sliding window approach. The proposed methodology encompasses rapid ground segmentation and the design of an iterative error-state Kalman filter (ESKF) to effectively fuse LiDAR point clouds and IMU measurements. By
Simultaneous Localization and Mapping (SLAM) is a significant research topic in robotics since it is one of the key technologies for robot automation. Although lidar-based SLAM methods have achieved promising performance, traditional lidar SLAM methods still produce large vertical errors. To address