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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14

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Paper Title: Reinforcement Learning-based DDPG and PRM Integration for Optimal Navigation in Varying Complex Environments
Authors Name: Dr. E. Madhusudan Raju , Cheruku Nikhil , Chanda Joshith
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IJRTI_204659
Published Paper Id: IJRTI2506164
Published In: Volume 10 Issue 6, June-2025
DOI: https://doi.org/10.56975/ijrti.v10i6.204659
Abstract: We have Autonomous navigation in various environments is critical for real-world applications. Adaptation to new environments and complexities is crucial for autonomous mobile robots. This project investigates feasibility of finding the optimal sample time and average reward structure for a given size of environment using Reinforcement Learning based Deep Deterministic Policy Gradient (DDPG) technique. This project finds the optimal connection distance and number of nodes to be given in finding the feasible path using Probabilistic Roadmap (PRM). Integrating these two techniques will enable a mobile robot to avoid obstacles while reaching the destination by following an optimal path. As a case study a mobile robot is trained using DDPG in three different environments of size 26x27 units with varying complexity. By varying sample time and reward, different agents were created. Analysis is done based on the obstacle avoidance and maximum distance travelled by mobile robot. By varying number of nodes and connection distance feasible paths found using PRM. By integrating these two DDPG and PRM techniques, the mobile robot path length to reach the destination is reduced by 40%.
Keywords: DDPG, PRM, Reinforcement Learning, Autonomous Navigation, Dynamic Environment
Cite Article: "Reinforcement Learning-based DDPG and PRM Integration for Optimal Navigation in Varying Complex Environments", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 6, page no.b536-b542, June-2025, Available :http://www.ijrti.org/papers/IJRTI2506164.pdf
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ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2506164
Registration ID:204659
Published In: Volume 10 Issue 6, June-2025
DOI (Digital Object Identifier): https://doi.org/10.56975/ijrti.v10i6.204659
Page No: b536-b542
Country: Hyderabad, Telangana, India
Research Area: Mechanical Engineering 
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2506164
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2506164
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

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