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This is a ROS package designed to implement Q-learning algorithm for the autonomous navigation of unmanned aerial vehicles (UAVs) in search-and-rescue (SaR) operations. It can also be used to train other reinforcement learning algorithms on UAVs. A PID algorithm is employed for position control.
This docker contains ROS Noetic and the environment to simulate the NASA Astrobee robot in the Internation Space Station Japanese Kibo Module. The simulation environment has all the necessary setup for the game scenario of the JAXA Kibo Robot Programming Challenge 2023.
This package provides a CLF-based reactive planning system, described in paper: Efficient Anytime CLF Reactive Planning System for a Bipedal Robot on Undulating Terrain. The reactive planning system consists of a 5-Hz planning thread to guide a robot to a distant goal and a 300-Hz Control-Lyapunov-Function-based (CLF-based) reactive thread to co…
A full simulation of a warehouse autonomous mobile robot that handles Orders and performing picking and delivery Products in a warehouse in Gazebo simulator.
This work proposes an anytime iterative system to concurrently solve the multi-objective path planning problem and determine the visiting order of destinations. The paper has been uploaded to arXiv at https://arxiv.org/abs/2205.14853