Multi-UAV Trajectory Optimization Utilizing a NURBS-Based Terrain Model for an Aerial Imaging Mission

• Published in: Journal of intelligent & robotic systems Vol. 97; no. 1; pp. 141 - 154
• Main Authors: Choi, Youngjun, Chen, Mengzhen, Choi, Younghoon, Briceno, Simon, Mavris, Dimitri
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 2020; Springer; Springer Nature B.V
• Subjects: Airborne sensing; Algorithms; Artificial Intelligence; Cloud computing; Computer simulation; Control; Electrical Engineering; Engineering; Imaging; Lidar; Mathematical optimization; Mechanical Engineering; Mechatronics; Numerical analysis; Optical radar; Remote sensing; Robotics; Route planning; Sensors; Specifications; Terrain; Terrain models; Three dimensional models; Topology optimization; Trajectory optimization; Unmanned aerial vehicles; Vehicle routing; Non-Uniform Rational B-Spline (NURBS); Multi-UAV trajectory optimization; Terrain modeling; Aerial imaging; Vehicle routing problem
• ISSN: 0921-0296; 1573-0409
• DOI: 10.1007/s10846-019-01027-9

Trajectory optimization precisely scanning an irregular terrain is a challenging problem since the trajectory optimizer needs to handle complex geometry topology, vehicle performance, and a sensor specification. To address these problems, this paper introduces a novel framework of a multi-UAV trajectory optimization method for an aerial imaging mission in an irregular terrain environment. The proposed framework consists of terrain modeling and multi-UAV trajectory optimization. The terrain modeling process employs a Non-Uniform Rational B-Spline (NURBS) surface fitting method based on point cloud information resulting from an airborne LiDAR sensor or other sensor systems. The NURBS-based surface model represents a computationally efficient terrain topology. In the trajectory optimization method, the framework introduces a multi-UAV vehicle routing problem enabling UAV to scan an entire area of interest, and obtains feasible trajectories based on given vehicle performance characteristics, and sensor specifications, and the approximated terrain model. The proposed multi-UAV trajectory optimization algorithm is tested by representative numerical simulations in a realistic aerial imaging environment, namely, San Diego and Death Valley, California.