Robot

Algorithm

Engineering

Aerospace engineering

Motion planning

Computer security

Archaeology

Range (aeronautics)

Obstacle avoidance

Incremental heuristic search

Computer science

Collision

Mathematical optimization

Collision avoidance

Beam search

Path length

Computer network

Obstacle

Mathematics

Geography

Mobile robot

Path (computing)

Artificial intelligence

Heuristic

Search algorithm

Programming language

Planner

Sensors

Based on a bio-heuristic algorithm, this paper proposes a novel path planner called obstacle avoidance beetle antennae search (OABAS) algorithm, which is applied to the global path planning of unmanned aerial vehicles (UAVs). Compared with the previous bio-heuristic algorithms, the algorithm proposed in this paper has advantages of a wide search range and breakneck search speed, which resolves the contradictory requirements of the high computational complexity of the bio-heuristic algorithm and real-time path planning of UAVs. Besides, the constraints used by the proposed algorithm satisfy various characteristics of the path, such as shorter path length, maximum allowed turning angle, and obstacle avoidance. Ignoring the z-axis optimization by combining with the minimum threat surface (MTS), the resultant path meets the requirements of efficiency and safety. The effectiveness of the algorithm is substantiated by applying the proposed path planning algorithm on the UAVs. Moreover, comparisons with other existing algorithms further demonstrate the superiority of the proposed OABAS algorithm.

Intelligent Beetle Antennae Search for UAV Sensing and Avoidance of Obstacles