UAV Path Planning for Area Coverage and Energy Consumption in Oil and Gas Exploration Environment

This paper proposes a model for unmanned aerial vehicles (UAV) gridbased coverage path planning, considering coverage completeness and energy consumption in complex environments with multiple obstacles. The work is inspired by the need for more efficient approaches to oil and gas exploration, but other application areas where UAVs can be used to explore unknown environments can also benefit from this work. An energy consumption model is proposed that considers acceleration, deceleration, and turning manoeuvres, as well as the distance to obstacles, to more accurately simulate the UAV's movement in different environments. Three different environments are modelled: desert, forest, and jungle. The energy-aware coverage path planning algorithm implemented seeks to reduce the energy consumption of a single drone while increasing coverage completeness. The model implementation and experiments were performed in the ROS/Gazebo simulation software. Obtained results show that the algorithm performs very well, with the drone able to manoeuvre itself in a combination of hills, valleys, rugged terrain, and steep topography while balancing coverage and energy consumption.