Open AccessEnergy-aware Coverage Path Planning for Unmanned Aerial Vehicles
Author(s) -
Tauã M. Cabreira,
Lisane Brisolara,
Paulo R. Ferreira
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/wtdr_ctdr.2020.14959
Subject(s) - patrolling , motion planning , energy consumption , computer science , drone , robotics , path (computing) , energy (signal processing) , real time computing , robot , grid , search and rescue , artificial intelligence , simulation , engineering , computer network , mathematics , geography , statistics , geometry , biology , electrical engineering , genetics , archaeology
Coverage Path Planning (CPP) problem is a motion planning subtopic in robotics, where it is necessary to build a path for a robot to explore every location in a given scenario. Unmanned Aerial Vehicles (UAV) have been employed in several applications related to the CPP problem. However, one of the significant limitations of UAVs is endurance, especially in multi-rotors. Minimizing energy consumption is pivotal to prolong and guarantee coverage. Thus, this work proposes energy-aware coverage path planning solutions for regular and irregular-shaped areas containing full and partial information. We consider aspects such as distance, time, turning maneuvers, and optimal speed in the UAV’s energy consumption. We propose an energy-aware spiral algorithm called E-Spiral to perform missions over regular-shaped areas. Next, we explore an energy-aware grid-based solution called EG-CPP for mapping missions over irregular-shaped areas containing no-fly zones. Finally, we present an energy-aware pheromone-based solution for patrolling missions called NC-Drone. The three novel approaches successfully address different coverage path planning scenarios, advancing the state-of-the-art in this area.