# TD3 Based Collision Free Motion Planning for Robot Navigation

arXiv: https://arxiv.org/abs/2405.15460 · HTML: https://mlsanity.com/paper/2405.15460/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- Placed in RL for robot navigation and UAV control, one of 15 directions in Deep reinforcement learning methods.
- Builds on 12 of its 22 references that are in the map.
- First posted on arXiv 24 May 2024.

## Placed in

- Deep reinforcement learning methods / [RL for robot navigation and UAV control](https://mlsanity.com/deeprl/rl-for-robot-navigation-and-uav-control/)

## Builds on (most cited first, 12 of 12)

- [Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review](https://mlsanity.com/paper/2402.10350/) (2024)
- [Particle Filter SLAM for Vehicle Localization](https://mlsanity.com/paper/2402.07429/) (2024)
- [Confidence Trigger Detection: Accelerating Real-time Tracking-by-detection Systems](https://mlsanity.com/paper/1902.00615/) (2019)
- [A Comparative Study on Enhancing Prediction in Social Network Advertisement through Data Augmentation](https://mlsanity.com/paper/2404.13812/) (2024)
- [Research on Splicing Image Detection Algorithms Based on Natural Image Statistical Characteristics](https://mlsanity.com/paper/2404.16296/) (2024)
- [Development and Application of a Monte Carlo Tree Search Algorithm for Simulating Da Vinci Code Game Strategies](https://mlsanity.com/paper/2403.10720/) (2024)
- [Text Sentiment Analysis and Classification Based on Bidirectional Gated Recurrent Units (GRUs) Model](https://mlsanity.com/paper/2404.17123/) (2024)
- [Segment Any Building](https://mlsanity.com/paper/2310.01164/) (2023)
- [Research on Detection of Floating Objects in River and Lake Based on AI Intelligent Image Recognition](https://mlsanity.com/paper/2404.06883/) (2024)
- [Optimization of Pressure Management Strategies for Geological CO2 Sequestration Using Surrogate Model-based Reinforcement Learning](https://mlsanity.com/paper/2403.07360/) (2024)
- [Semi-supervised multiscale dual-encoding method for faulty traffic data detection](https://mlsanity.com/paper/2212.13596/) (2022)
- [Enhancing user experience in large language models through human-centered design: Integrating theoretical insights with an experimental study to meet diverse software learning needs with a single document knowledge base](https://mlsanity.com/paper/2405.11505/) (2024)

## Built on by (most cited first, 20 of 20)

- [A Survey of Sim-to-Real Methods in RL: Progress, Prospects and Challenges with Foundation Models](https://mlsanity.com/paper/2502.13187/) (2025)
- [Deep Learning-based Anomaly Detection and Log Analysis for Computer Networks](https://mlsanity.com/paper/2407.05639/) (2024)
- [Image anomaly detection and prediction scheme based on SSA optimized ResNet50-BiGRU model](https://mlsanity.com/paper/2406.13987/) (2024)
- [Autonomous Navigation of Unmanned Vehicle Through Deep Reinforcement Learning](https://mlsanity.com/paper/2407.18962/) (2024)
- [Advanced User Credit Risk Prediction Model using LightGBM, XGBoost and Tabnet with SMOTEENN](https://mlsanity.com/paper/2408.03497/) (2024)
- [Advanced AI Framework for Enhanced Detection and Assessment of Abdominal Trauma: Integrating 3D Segmentation with 2D CNN and RNN Models](https://mlsanity.com/paper/2407.16165/) (2024)
- [Research on the Design of a Short Video Recommendation System Based on Multimodal Information and Differential Privacy](https://mlsanity.com/paper/2504.08751/) (2025)
- [Optimized CNNs for Rapid 3D Point Cloud Object Recognition](https://mlsanity.com/paper/2412.02855/) (2024)
- [Real-time Video Target Tracking Algorithm Utilizing Convolutional Neural Networks (CNN)](https://mlsanity.com/paper/2411.18314/) (2024)
- [Artistic Neural Style Transfer Algorithms with Activation Smoothing](https://mlsanity.com/paper/2411.08014/) (2024)
- [Transforming Movie Recommendations with Advanced Machine Learning: A Study of NMF, SVD,and K-Means Clustering](https://mlsanity.com/paper/2407.08916/) (2024)
- [Enhancing Exchange Rate Forecasting with Explainable Deep Learning Models](https://mlsanity.com/paper/2410.19241/) (2024)
- [Dynamic Optimization of Storage Systems Using Reinforcement Learning Techniques](https://mlsanity.com/paper/2501.00068/) (2024)
- [3D RL-DWA: A Hybrid Reinforcement Learning and Dynamic Window Approach for Goal-Directed Local Navigation in Multi-DoF Robots](https://mlsanity.com/paper/2605.12689/) (2026)
- [International Trade Flow Prediction with Bilateral Trade Provisions](https://mlsanity.com/paper/2407.13698/) (2024)
- [Innovative Deep Learning Techniques for Obstacle Recognition: A Comparative Study of Modern Detection Algorithms](https://mlsanity.com/paper/2410.10096/) (2024)
- [Cutting-Edge Detection of Fatigue in Drivers: A Comparative Study of Object Detection Models](https://mlsanity.com/paper/2410.15030/) (2024)
- [Construction and optimization of health behavior prediction model for the elderly in smart elderly care](https://mlsanity.com/paper/2412.02062/) (2024)
- [SafeMove-RL: A Certifiable Reinforcement Learning Framework for Dynamic Motion Constraints in Trajectory Planning](https://mlsanity.com/paper/2505.12648/) (2025)
- [Optimizing Path Planning using Deep Reinforcement Learning for UGVs in Precision Agriculture](https://mlsanity.com/paper/2601.04668/) (2026)

## Abstract (arXiv)

This paper addresses the challenge of collision-free motion planning in automated navigation within complex environments. Utilizing advancements in Deep Reinforcement Learning (DRL) and sensor technologies like LiDAR, we propose the TD3-DWA algorithm, an innovative fusion of the traditional Dynamic Window Approach (DWA) with the Twin Delayed Deep Deterministic Policy Gradient (TD3). This hybrid algorithm enhances the efficiency of robotic path planning by optimizing the sampling interval parameters of DWA to effectively navigate around both static and dynamic obstacles. The performance of the TD3-DWA algorithm is validated through various simulation experiments, demonstrating its potential to significantly improve the reliability and safety of autonomous navigation systems.