Cover Image

Mixed-Reality Digital Twins: Leveraging the Physical and Virtual Worlds for Hybrid Sim2Real Transition of Multi-Agent Reinforcement Learning Policies

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Samak, Chinmay Vilas, Samak, Tanmay Vilas, Krovi, Venkat Narayan
Format:	Preprint
Published:	2024
Subjects:	Robotics Machine Learning Multiagent Systems
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Towards Validation of Autonomous Vehicles Across Scales using an Integrated Digital Twin Framework
by: Samak, Tanmay Vilas, et al.
Published: (2024)

Metaverse for Safer Roadways: An Immersive Digital Twin Framework for Exploring Human-Autonomy Coexistence in Urban Transportation Systems
by: Samak, Tanmay Vilas, et al.
Published: (2024)

Towards Sim2Real Transfer of Autonomy Algorithms using AutoDRIVE Ecosystem
by: Samak, Chinmay Vilas, et al.
Published: (2023)

Sim2Real Diffusion: Leveraging Foundation Vision Language Models for Adaptive Automated Driving
by: Samak, Chinmay Vilas, et al.
Published: (2025)

Autonomy Oriented Digital Twins for Real2Sim2Real Autoware Deployment
by: Samak, Chinmay Vilas, et al.
Published: (2024)

When Digital Twins Meet Large Language Models: Realistic, Interactive, and Editable Simulation for Autonomous Driving
by: Samak, Tanmay Vilas, et al.
Published: (2025)

Nigel -- Mechatronic Design and Robust Sim2Real Control of an Over-Actuated Autonomous Vehicle
by: Samak, Chinmay Vilas, et al.
Published: (2024)

Towards Mechatronics Approach of System Design, Verification and Validation for Autonomous Vehicles
by: Samak, Chinmay Vilas, et al.
Published: (2023)

Digital Twins Meet the Koopman Operator: Data-Driven Learning for Robust Autonomy
by: Samak, Chinmay Vilas, et al.
Published: (2024)

Digital Twins in the Cloud: A Modular, Scalable and Interoperable Framework for Accelerating Verification and Validation of Autonomous Driving Solutions
by: Samak, Tanmay Vilas, et al.
Published: (2025)

Off-Road Autonomy Validation Using Scalable Digital Twin Simulations Within High-Performance Computing Clusters
by: Samak, Tanmay Vilas, et al.
Published: (2024)

A Systematic Digital Engineering Approach to Verification & Validation of Autonomous Ground Vehicles in Off-Road Environments
by: Samak, Tanmay Vilas, et al.
Published: (2025)

Leveraging Partial Symmetry for Multi-Agent Reinforcement Learning
by: Yu, Xin, et al.
Published: (2023)

Prompt Informed Reinforcement Learning for Visual Coverage Path Planning
by: Margapuri, Venkat
Published: (2025)

Multi-Agent Inverse Reinforcement Learning in Real World Unstructured Pedestrian Crowds
by: Chandra, Rohan, et al.
Published: (2024)

Budget Allocation Policies for Real-Time Multi-Agent Path Finding
by: Beck, Raz, et al.
Published: (2025)

Beyond Joint Demonstrations: Personalized Expert Guidance for Efficient Multi-Agent Reinforcement Learning
by: Yu, Peihong, et al.
Published: (2024)

Human-guided Swarms: Impedance Control-inspired Influence in Virtual Reality Environments
by: Barclay, Spencer, et al.
Published: (2024)

Optimizing UAV-UGV Coalition Operations: A Hybrid Clustering and Multi-Agent Reinforcement Learning Approach for Path Planning in Obstructed Environment
by: Brotee, Shamyo, et al.
Published: (2024)

Dynamic Deep Factor Graph for Multi-Agent Reinforcement Learning
by: Shi, Yuchen, et al.
Published: (2024)

Subgoal-based Hierarchical Reinforcement Learning for Multi-Agent Collaboration
by: Xu, Cheng, et al.
Published: (2024)

Physics-Informed Multi-Agent Reinforcement Learning for Distributed Multi-Robot Problems
by: Sebastian, Eduardo, et al.
Published: (2023)

Cooperative Hybrid Multi-Agent Pathfinding Based on Shared Exploration Maps
by: Liu, Ning, et al.
Published: (2025)

From Abstraction to Reality: DARPA's Vision for Robust Sim-to-Real Autonomy
by: Noorani, Erfaun, et al.
Published: (2025)

Exploring 6G Potential for Industrial Digital Twinning and Swarm Intelligence in Obstacle-Rich Environments
by: Yuan, Siyu, et al.
Published: (2024)

Robust and Safe Multi-Agent Reinforcement Learning with Communication for Autonomous Vehicles: From Simulation to Hardware
by: Smith, Keshawn, et al.
Published: (2025)

Multi-Agent Reinforcement Learning for Connected and Automated Vehicles Control: Recent Advancements and Future Prospects
by: Hua, Min, et al.
Published: (2023)

Safety Guaranteed Robust Multi-Agent Reinforcement Learning with Hierarchical Control for Connected and Automated Vehicles
by: Zhang, Zhili, et al.
Published: (2023)

Active Sensing Strategy: Multi-Modal, Multi-Robot Source Localization and Mapping in Real-World Settings with Fixed One-Way Switching
by: Tran, Vu Phi, et al.
Published: (2024)

HIPPO-MAT: Decentralized Task Allocation Using GraphSAGE and Multi-Agent Deep Reinforcement Learning
by: Ratnabala, Lavanya, et al.
Published: (2025)

Evader-Agnostic Team-Based Pursuit Strategies in Partially-Observable Environments
by: Kalanther, Addison, et al.
Published: (2025)

Cooperation and Fairness in Multi-Agent Reinforcement Learning
by: Aloor, Jasmine Jerry, et al.
Published: (2024)

MARVEL: Multi-Agent Reinforcement Learning for constrained field-of-View multi-robot Exploration in Large-scale environments
by: Chiun, Jimmy, et al.
Published: (2025)

Leveraging Large Language Models for Effective and Explainable Multi-Agent Credit Assignment
by: Nagpal, Kartik, et al.
Published: (2025)

Learning to Change: Choreographing Mixed Traffic Through Lateral Control and Hierarchical Reinforcement Learning
by: Wang, Dawei, et al.
Published: (2024)

Multi-Agent Vulcan: An Information-Driven Multi-Agent Path Finding Approach
by: Olkin, Jake, et al.
Published: (2024)

SceneFactory: GPU-Accelerated Multi-Agent Driving Simulation with Physics-Based Vehicle Dynamics
by: Zhu, Yicheng, et al.
Published: (2026)

Discovery and Deployment of Emergent Robot Swarm Behaviors via Representation Learning and Real2Sim2Real Transfer
by: Mattson, Connor, et al.
Published: (2025)

Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey
by: Zhang, Ruiqi, et al.
Published: (2024)

Co-Optimizing Reconfigurable Environments and Policies for Decentralized Multi-Agent Navigation
by: Gao, Zhan, et al.
Published: (2024)