Gazebo
Emerging8papers using it
2024first seen
The 'Gazebo' dataset/benchmark is used to evaluate the performance of autonomous systems, specifically in the context of navigation and manipulation tasks in unstructured environments.
Papers using Gazebo (8)
- Regularized Reward-Punishment Reinforcement LearningScaling Multi Agent Reinforcement Learning for Underwater Acoustic Tracking via Autonomous VehiclesDRL-Based Pose Control for Double-Ackermann Robots Under Actuation UncertaintiesLLM-Foraging: Large Language Models for Decentralized Swarm Robot ForagingHeterogeneous Multi-Expert Reinforcement Learning for Long-Horizon Multi-Goal Tasks in Autonomous ForkliftsShared Control of Holonomic Wheelchairs through Reinforcement LearningEDEN: Entorhinal Driven Egocentric Navigation Toward Robotic DeploymentLearning Manipulation Tasks in Dynamic and Shared 3D Spaces