Collision Avoidance and Navigation for a Quadrotor Swarm Using End-to-end Deep Reinforcement Learning

no code implementations • 23 Sep 2023 • Zhehui Huang, Zhaojing Yang, Rahul Krupani, Baskın Şenbaşlar, Sumeet Batra, Gaurav S. Sukhatme

In this work, we propose an end-to-end DRL approach to control quadrotor swarms in environments with obstacles.

Collision Avoidance

QuadSwarm: A Modular Multi-Quadrotor Simulator for Deep Reinforcement Learning with Direct Thrust Control

1 code implementation • 15 Jun 2023 • Zhehui Huang, Sumeet Batra, Tao Chen, Rahul Krupani, Tushar Kumar, Artem Molchanov, Aleksei Petrenko, James A. Preiss, Zhaojing Yang, Gaurav S. Sukhatme

In addition to speed, such simulators need to model the physics of the robots and their interaction with the environment to a level acceptable for transferring policies learned in simulation to reality.

Reinforcement Learning (RL)

Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning

no code implementations • 23 May 2023 • Sumeet Batra, Bryon Tjanaka, Matthew C. Fontaine, Aleksei Petrenko, Stefanos Nikolaidis, Gaurav Sukhatme

Training generally capable agents that thoroughly explore their environment and learn new and diverse skills is a long-term goal of robot learning.

reinforcement-learning Reinforcement Learning (RL)

Augmented Reality for Human-Swarm Interaction in a Swarm-Robotic Chemistry Simulation

no code implementations • 2 Dec 2019 • Sumeet Batra, John Klingner, Nikolaus Correll

We present a method to register individual members of a robotic swarm in an augmented reality display while showing relevant information about swarm dynamics to the user that would be otherwise hidden.