Multi-task Allocation Framework with Spatial Dislocation Collision Avoidance for Multiple Aerial Robots

Tingjun Lei, Mississippi State University
Chaomin Luo, Mississippi State University
Timothy Sellers, Mississippi State University
Ying Wang, Kennesaw State University


Multi-task allocation and trajectory planning for multiple unmanned aerial vehicles (UAVs) have been extensively used in various real-world applications. This paper presents a framework of multi-UAV multi-task allocation and trajectory planning with collision avoidance. The scenario of interest is one where multiple UAVs are launched in order to investigate selected targets in a massive wildfire disaster relief terrain. Initially, one UAV is launched to search wildfire locations and wildfire lines by a developed informative path planning algorithm. An informative exploratory search mechanism is developed that provides the exploration trajectories to precisely locate the wildfire positions in the wildfire environments. Afterwards, with the investigated environmental information including GPS coordinates of wildfire positions and distribution as targets, UAVs are deployed to multiple target positions. In order to perform effective collision avoidance, a spatial dislocation scheme is developed by introduction of an additional dimension for UAVs at different altitudes, whereas UAVs avoid collision at the same altitude using a proposed velocity profile paradigm. Concurrent multi-task allocation, trajectory planning, and collision avoidance are successfully carried out with unequal numbers of UAVs and targets. The proposed framework has been validated by simulation studies and comparative analyses.