mlsanityData to 14 Oct 2026

PIC4rl-gym: a ROS2 modular framework for Robots Autonomous Navigation with Deep Reinforcement Learning

arXiv 2211.10714 ↗First posted 19 Nov 2022cs.RO cs.AIcited by 4

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Abstract (arXiv)

Learning agents can optimize standard autonomous navigation improving flexibility, efficiency, and computational cost of the system by adopting a wide variety of approaches. This work introduces the textitPIC4rl-gym, a fundamental modular framework to enhance navigation and learning research by mixing ROS2 and Gazebo, the standard tools of the robotics community, with Deep Reinforcement Learning (DRL). The paper describes the whole structure of the PIC4rl-gym, which fully integrates DRL agent's training and testing in several indoor and outdoor navigation scenarios and tasks. A modular approach is adopted to easily customize the simulation by selecting new platforms, sensors, or models. We demonstrate the potential of our novel gym by benchmarking the resulting policies, trained for different navigation tasks, with a complete set of metrics.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 16 of its 19 references that are in the map. First posted on arXiv 19 Nov 2022.

Builds on

16 of 19 references.

References · 16

  1. 2018Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actorcited by 4,885
  2. 2015Continuous control with deep reinforcement learningcited by 3,407
  3. 2018Addressing Function Approximation Error in Actor-Critic Methodscited by 2,417
  4. 2022Robot Operating System 2: Design, Architecture, and Uses In The Wildcited by 199
  5. 2017Socially Aware Motion Planning with Deep Reinforcement Learningcited by 136
  6. 2021Autonomous Drone Racing with Deep Reinforcement Learningcited by 60
  7. 2020Benchmarking Metric Ground Navigationcited by 20
  8. 2021APPL: Adaptive Planner Parameter Learningcited by 20
  9. 2020Dynamically Feasible Deep Reinforcement Learning Policy for Robot Navigation in Dense Mobile Crowdscited by 16
  10. 2020APPLR: Adaptive Planner Parameter Learning from Reinforcementcited by 16
  11. 2022Position-Agnostic Autonomous Navigation in Vineyards with Deep Reinforcement Learningcited by 11
  12. 2019gym-gazebo2, a toolkit for reinforcement learning using ROS 2 and Gazebocited by 7
4 more
  1. 2021Marvin: an Innovative Omni-Directional Robotic Assistant for Domestic Environmentscited by 6
  2. 2022RL-DWA Omnidirectional Motion Planning for Person Following in Domestic Assistance and Monitoringcited by 2
  3. 2019ROS2Learn: a reinforcement learning framework for ROS 2cited by 1
  4. 2022DeepSim: A Reinforcement Learning Environment Build Toolkit for ROS and Gazebocited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 1; 2025: 1; 2026: 1.

4 papers.

  1. 2025Socially aware navigation for mobile robots: a survey on deep reinforcement learning approachescited by 2
  2. 2024Adaptive Social Force Window Planner with Reinforcement Learningcited by 1
  3. 2023Enhancing Navigation Benchmarking and Perception Data Generation for Row-based Crops in Simulationcited by 0
  4. 2026GzDRL: Reproducible and Scalable Deep Reinforcement Learning with Gazebocited by 0