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access icon free Path planning for UAV/UGV collaborative systems in intelligent manufacturing

© The Institution of Engineering and Technology
Received 19/10/2019, Accepted 04/05/2020, Revised 19/04/2020, Published 12/05/2020

Due to the development needs of the intelligent manufacturing industry, the use of drones is expanding indefinitely, and at the same time, extremely high requirements are imposed on the autonomous navigation of drones to reduce human intervention. This paper presents an UAV/ UGV scheduling problem in which the UAV needs to be recharged by the UGV in order to working in persistent tasks, and meanwhile, the UGV need to visits UGV working depots. Two different problem are presented: fixed charging sets problem (FCSP) and discrete charging sets problem (DCSP). In FCSP, charging sets are fixed, and a two-stage travelling salesman problem method is proposed to solve the problem. DCSP is a modification of FCSP while charging segments are discrete into serval segments, an graph transformation approach was proposed to transform DCSP into GTSP, so DCSP can be resolved by using GTSP solvers. Simulation results shows that both DCSP and FCSP can ensure UAV/UGV work in persistent tasks, and the graph transformation algorithm can efficiently transform DCSP into GTSP.

Inspec keywords: autonomous aerial vehicles; path planning; graph theory; remotely operated vehicles; travelling salesman problems; mobile robots

Other keywords: path planning; charging sets problem; autonomous navigation; intelligent manufacturing industry; FCSP; two-stage travelling salesman problem method; generalised travelling salesman problem; extremely high requirements; charging routes; drones; attitude tracking function; DCSP; charging segments

Subjects: Combinatorial mathematics; Aerospace control; Spatial variables control; Telerobotics; Optimisation techniques; Mobile robots

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