Numerical Potential Fields Based Multi-stage Path Planning for UTM in Dense Non-segregated Airspace

• Published in: Journal of intelligent & robotic systems Vol. 109; no. 1; p. 5
• Main Authors: M A, Sajid Ahamed, K, Satya Prakash, Jana, Shuvrangshu, Ghose, Debasish
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.09.2023; Springer Nature B.V
• Subjects: Air traffic management; Air transportation; Aircraft; Airspace; Algorithms; Artificial Intelligence; Collision avoidance; Control; Density; Electrical Engineering; Engineering; Low altitude; Mechanical Engineering; Mechatronics; Path planning; Payloads; Potential fields; Robotics; Segregation; Short Paper; Transportation systems; Unmanned aerial vehicles; Unmanned aircraft; Urban environments; Dynamic zone partitioning; Numerical potential field; UAS Traffic Management (UTM); Local collision avoidance; Unmanned aircraft system (UAS)
• ISSN: 0921-0296; 1573-0409
• DOI: 10.1007/s10846-023-01916-0

This paper addresses the problem of Unmanned Aircraft System Traffic Management (UTM), which refers to an air transportation system wherein unmanned aircraft systems (UAS) are used to deliver small payloads on-demand by safely maneuvering in the low-altitude known urban infrastructure inhabited by dynamic air traffic. A multi-stage framework based on numerical potential fields is proposed for establishing UTM in the non-segregated airspace. Numerical potential fields are adopted for global path planning as they provide optimum stand-off clearance from obstacles in the environment. The proposed global path planning approach is augmented with a prediction-based zone determination algorithm to minimize high-density air traffic encounters by the UAS. In the event of low-density traffic in the vicinity of the UAS, the UAS neighborhood is sectorized into octants. An octant-based local collision avoidance strategy generates force fields that divert the UAS into a vacant octant. Extensive simulations have been carried out to show the efficacy of the proposed method in dense urban settings.