mlsanityData to 7 Oct 2026

Autonomous Navigation of Unmanned Vehicle Through Deep Reinforcement Learning

arXiv 2407.18962 ↗First posted 18 Jul 2024cs.RO cs.LGcited by 12

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Abstract (arXiv)

This paper explores the method of achieving autonomous navigation of unmanned vehicles through Deep Reinforcement Learning (DRL). The focus is on using the Deep Deterministic Policy Gradient (DDPG) algorithm to address issues in high-dimensional continuous action spaces. The paper details the model of a Ackermann robot and the structure and application of the DDPG algorithm. Experiments were conducted in a simulation environment to verify the feasibility of the improved algorithm. The results demonstrate that the DDPG algorithm outperforms traditional Deep Q-Network (DQN) and Double Deep Q-Network (DDQN) algorithms in path planning tasks.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 15 of its 33 references that are in the map. First posted on arXiv 18 Jul 2024.

Builds on

15 of 33 references.

References · 15

  1. 2024Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitatecited by 46
  2. 2024APEER: Automatic Prompt Engineering Enhances Large Language Model Rerankingcited by 28
  3. 2023MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Trainingcited by 25
  4. 2024Theoretical Analysis of Meta Reinforcement Learning: Generalization Bounds and Convergence Guaranteescited by 22
  5. 2024TD3 Based Collision Free Motion Planning for Robot Navigationcited by 18
  6. 2023MEGA-DAgger: Imitation Learning with Multiple Imperfect Expertscited by 17
  7. 2024Enhanced Detection Classification via Clustering SVM for Various Robot Collaboration Taskcited by 17
  8. 2024Incremental Joint Learning of Depth, Pose and Implicit Scene Representation on Monocular Camera in Large-scale Scenescited by 15
  9. 2024DeepGI: An Automated Approach for Gastrointestinal Tract Segmentation in MRI Scanscited by 13
  10. 2022A Benchmark Comparison of Imitation Learning-based Control Policies for Autonomous Racingcited by 11
  11. 2024Deep Learning Powered Estimate of The Extrinsic Parameters on Unmanned Surface Vehiclescited by 9
  12. 2024Development and Application of a Monte Carlo Tree Search Algorithm for Simulating Da Vinci Code Game Strategiescited by 8
3 more
  1. 2024Optimization of Pressure Management Strategies for Geological CO2 Sequestration Using Surrogate Model-based Reinforcement Learningcited by 4
  2. 2024Advanced Multimodal Deep Learning Architecture for Image-Text Matchingcited by 4
  3. 2022Assessment of U.S. Department of Transportation Lane-Level Map for Connected Vehicle Applicationscited by 1

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Cited by year

Citing papers per year: 2024: 7; 2025: 5.

12 papers.

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  2. 2025Enhancing Intent Understanding for Ambiguous prompt: A Human-Machine Co-Adaption Strategycited by 16
  3. 2024LoRA-LiteE: A Computationally Efficient Framework for Chatbot Preference-Tuningcited by 10
  4. 2024Enhanced Recommendation Combining Collaborative Filtering and Large Language Modelscited by 10
  5. 2024LProtector: An LLM-driven Vulnerability Detection Systemcited by 8
  6. 2024Real-time Video Target Tracking Algorithm Utilizing Convolutional Neural Networks (CNN)cited by 4
  7. 2024Artistic Neural Style Transfer Algorithms with Activation Smoothingcited by 3
  8. 2024Enhancing Exchange Rate Forecasting with Explainable Deep Learning Modelscited by 2
  9. 2025Efficient Temporal Consistency in Diffusion-Based Video Editing with Adaptor Modules: A Theoretical Frameworkcited by 2
  10. 2025TDRI: Two-Phase Dialogue Refinement and Co-Adaptation for Interactive Image Generationcited by 1
  11. 2025Taxonomy and Trends in Reinforcement Learning for Robotics and Control Systems: A Structured Reviewcited by 0
  12. 2025Hybrid DQN-TD3 Reinforcement Learning for Autonomous Navigation in Dynamic Environmentscited by 0