Time-Efficient Mars Exploration of Simultaneous Coverage and Charging with Multiple Drones
This work addresses the challenge of autonomous and efficient exploration in extraterrestrial environments like Mars, which is incremental as it combines existing methods like deep reinforcement learning with novel scheduling for a specific application.
This paper tackles the problem of time-efficient Mars surface exploration using multiple drones and a rover by developing the TIME-SC2 framework, which integrates coverage control and charging scheduling to maximize long-term coverage while handling energy and safety constraints, achieving high autonomy and reduced non-exploring time in simulations.
This paper presents a time-efficient scheme for Mars exploration by the cooperation of multiple drones and a rover. To maximize effective coverage of the Mars surface in the long run, a comprehensive framework has been developed with joint consideration for limited energy, sensor model, communication range and safety radius, which we call TIME-SC2 (TIme-efficient Mars Exploration of Simultaneous Coverage and Charging). First, we propose a multi-drone coverage control algorithm by leveraging emerging deep reinforcement learning and design a novel information map to represent dynamic system states. Second, we propose a near-optimal charging scheduling algorithm to navigate each drone to an individual charging slot, and we have proven that there always exists feasible solutions. The attractiveness of this framework not only resides on its ability to maximize exploration efficiency, but also on its high autonomy that has greatly reduced the non-exploring time. Extensive simulations have been conducted to demonstrate the remarkable performance of TIME-SC2 in terms of time-efficiency, adaptivity and flexibility.