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Extending the Range of Drone-based Delivery Services by Exploration
Drones have a fairly short range due to their limited battery life. We p...
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Auction-based Charging Scheduling with Deep Learning Framework for Multi-Drone Networks
State-of-the-art drone technologies have severe flight time limitations ...
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Efficient Drone Mobility Support Using Reinforcement Learning
Flying drones can be used in a wide range of applications and services f...
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Exploration in NetHack with Secret Discovery
Roguelike games generally feature exploration problems as a critical, ye...
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Visualizing Sensor Network Coverage with Location Uncertainty
We present an interactive visualization system for exploring the coverag...
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An Efficient Transition Algorithm For Seamless Drone Multicasting
Many drone-related applications (e.g., drone-aided video capture, drone ...
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Distributed Wildfire Surveillance with Autonomous Aircraft using Deep Reinforcement Learning
Teams of autonomous unmanned aircraft can be used to monitor wildfires, ...
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Time-Efficient Mars Exploration of Simultaneous Coverage and Charging with Multiple Drones
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.
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