Enhancing Human-Robot Collaboration Through Adaptive Reinforcement Learning
Parmar DhavalKumar LaljeeBhai
, Chauhan Devang , Khyati Joshi
- Human-Robot Collaboration, Adaptive Reinforcement Learning, Human-Centered Robotics, Robot Learning, Intelligent Systems, Human-Robot Interaction (HRI), Adaptive Systems, Collaborative Robotics
Human-Robot Collaboration (HRC) is becoming increasingly important in industries such as domestic services, healthcare, and manufacturing. This study explores the use of Adaptive Reinforcement Learning (ARL), which enables robots to learn and improve their actions through real-time human feedback and situational context. We propose a unique ARL-based framework that enhances robots’ understanding of human intentions and allows for co-learning and co-adaptation. The findings demonstrate how ARL can transform HRC by combining robotic precision with human expertise.
"Enhancing Human-Robot Collaboration Through Adaptive Reinforcement Learning", TIJER - TIJER - INTERNATIONAL RESEARCH JOURNAL (www.TIJER.org), ISSN:2349-9249, Vol.12, Issue 4, page no.a138-a141, April-2025, Available :https://tijer.org/TIJER/papers/TIJER2504021.pdf
Volume 12
Issue 4,
April-2025
Pages : a138-a141
Paper Reg. ID: TIJER_157311
Published Paper Id: TIJER2504021
Downloads: 000296
Research Area: Science and Technology
Country: Rajkot, Gujarat, India
ISSN: 2349-9249 | IMPACT FACTOR: 8.57 Calculated By Google Scholar | ESTD YEAR: 2014
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: TIJER (IJ Publication) Janvi Wave
