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A multi-robot foraging model on deciding predation risk vs. food quality trade-offs.

, , and . ROBIO, page 1192-1197. IEEE, (2014)

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A Reinforcement Learning Approach to Jointly Adapt Vehicular Communications and Planning for Optimized Driving., , , , , and . ITSC, page 3287-3293. IEEE, (2018)UAV Target Tracking in Urban Environments Using Deep Reinforcement Learning., and . CoRR, (2020)A Low-Cost Monocular Vision-Based Obstacle Avoidance Using SVM and Optical Flow., , and . Unmanned Syst., 6 (4): 267-275 (2018)Optimization of Wireless Sensor Network and UAV Data Acquisition., , , , and . J. Intell. Robotic Syst., 78 (1): 159-179 (2015)Optimal Rendezvous Trajectory for Unmanned Aerial-Ground Vehicles., , , , and . IEEE Trans. Aerosp. Electron. Syst., 54 (2): 834-847 (2018)Visibility-Aware Navigation With Batch Projection Augmented Cross-Entropy Method Over a Learned Occlusion Cost., , , , , and . IEEE Robotics Autom. Lett., 7 (4): 9366-9373 (2022)Visibility-Based Monitoring of a Path Using a Heterogeneous Robot Team., , , and . IROS, page 3765-3770. IEEE, (2018)Graph-based Prediction and Planning Policy Network (GP3Net) for scalable self-driving in dynamic environments using Deep Reinforcement Learning., , , and . CoRR, (2023)Multi-UAV task allocation with communication faults., and . ACC, page 3724-3729. IEEE, (2012)A virtual bug planning technique for 2D robot path planning., , , and . ACC, page 5062-5069. IEEE, (2018)