Collision Avoidance and Navigation for a Quadrotor Swarm Using End-to-end Deep Reinforcement Learning
Zhehui Huang,Zhaojing Yang,Rahul Krupani,Baskın Şenbaşlar,Sumeet Batra,Gaurav S. Sukhatme,Zhehui Huang,Zhaojing Yang,Rahul Krupani,Baskın Şenbaşlar,Sumeet Batra,Gaurav S. Sukhatme
End-to-end deep reinforcement learning (DRL) for quadrotor control promises many benefits – easy deployment, task generalization and real-time execution capability. Prior end-to-end DRL-based methods have showcased the ability to deploy learned controllers onto single quadrotors or quadrotor teams maneuvering in simple, obstacle-free environments. However, the addition of obstacles increases the n...
