Identification and Avoidance of Static and Dynamic Obstacles on Point Cloud for UAVs Navigation
Avoiding hybrid obstacles in unknown scenarios with an efficient flight strategy is a key challenge for unmanned aerial vehicle applications. In this paper, we introduce a technique to distinguish dynamic obstacles from static ones with only point cloud input. Then, a computationally efficient obstacle avoidance motion planning approach is proposed and it is in line with an improved relative velocity method. The approach is able to avoid both static obstacles and dynamic ones in the same framework. For static and dynamic obstacles, the collision check and motion constraints are different, and they are integrated into one framework efficiently. In addition, we present several techniques to improve the algorithm performance and deal with the time gap between different submodules. The proposed approach is implemented to run onboard in real-time and validated extensively in simulation and hardware tests. Our average single step calculating time is less than 20 ms.
Code (0)
등록된 구현이 없습니다.
Tasks
Motion PlanningSimilar Papers 제목 키워드 기반
Obstacle Identification and Ellipsoidal Decomposition for Fast Motion Planning in Unknown Dynamic Environments
Collision avoidance in the presence of dynamic obstacles in unknown environments is one of the most critical challenges for unmanned systems. In this paper, we present a method that identifies obstacles in terms of ellip…
Collision AvoidanceMotion PlanningIndoor Navigation Assistance for Visually Impaired People via Dynamic SLAM and Panoptic Segmentation with an RGB-D Sensor
Exploring an unfamiliar indoor environment and avoiding obstacles is challenging for visually impaired people. Currently, several approaches achieve the avoidance of static obstacles based on the mapping of indoor scenes…
Motion EstimationObjectPanoptic SegmentationTrajectory Planning with Model Predictive Control for Obstacle Avoidance Considering Prediction Uncertainty
This paper introduces a novel trajectory planner for autonomous robots, specifically designed to enhance navigation by incorporating dynamic obstacle avoidance within the Robot Operating System 2 (ROS2) and Navigation 2 …
Collision AvoidanceModel Predictive ControlNavigateTrajectory PlanningVision-aided UAV navigation and dynamic obstacle avoidance using gradient-based B-spline trajectory optimization
Navigating dynamic environments requires the robot to generate collision-free trajectories and actively avoid moving obstacles. Most previous works designed path planning algorithms based on one single map representation…
NavigateA real-time dynamic obstacle tracking and mapping system for UAV navigation and collision avoidance with an RGB-D camera
The real-time dynamic environment perception has become vital for autonomous robots in crowded spaces. Although the popular voxel-based mapping methods can efficiently represent 3D obstacles with arbitrarily complex shap…
Autonomous DrivingCollision AvoidanceTrajectory Prediction