Abstract
A reactive three-dimensional maneuver strategy for a multirotor Unmanned Aerial Vehicle (UAV) is proposed based on the collision cone approach to avoid potential collision with a single moving obstacle detected by an onboard sensor. A Light Detection And Ranging (LiDAR) system is assumed to be mounted on a hexacopter to obtain the obstacle information from the collected point clouds. The collision cone approach is enhanced to appropriately deal with the moving obstacle with the help of a Kalman filter. The filter estimates the position, velocity, and acceleration of the obstacle by using the LiDAR data as the associated measurement. The obstacle state estimate is utilized to predict the future trajectories of the moving obstacle. The collision detection and obstacle avoidance maneuver decisions are made considering the predicted trajectory of the obstacle. Numerical simulations, including a Monte Carlo campaign, are conducted to verify the performance of the proposed collision avoidance algorithm.
Highlights
In the last decade, Unmanned Aerial Vehicles (UAVs) have achieved significant advances in scientific research as well as in real-world applications
If the velocity vector of the hexacopter is contained within the collision cone, the detected obstacle is a potential threat to the UAV unless it changes its trajectory
The algorithm is based on the collision cone approach, and is improved to handle a moving obstacle by considering the short-term predictions for the obstacle trajectory with the aid of an obstacle state estimator
Summary
In the last decade, Unmanned Aerial Vehicles (UAVs) have achieved significant advances in scientific research as well as in real-world applications. Hening et al [14] presented a data fusion technique for the position and velocity estimation of UAVs. Local position information was provided by a LiDAR sensor, and an adaptive Kalman filter was applied for the integration. The guidance law of the UAV was made applicable for moving obstacles by incorporating the Point of Closest Approach (PCA). If a potential collision is detected, the state estimate is used to generate aiming point candidates for the avoidance maneuver. The proposed algorithm removes the candidate points that overlap with the predicted path of the obstacle This enables the hexacopter to consider the kinematics of the obstacle in choosing the direction of the avoidance maneuver.
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