40 citations · 167 across the 22 of their papers we have counts for
23 papers
When Digital Twins Meet Large Language Models: Realistic, Interactive, and Editable Simulation for Autonomous Driving
Tanmay Vilas Samak, Chinmay Vilas Samak, Bing Li +1
Simulation frameworks have been key enablers for the development and validation of autonomous driving systems. However, existing methods struggle to comprehensively address the aut…
Sim2Real Diffusion: Leveraging Foundation Vision Language Models for Adaptive Automated Driving
Chinmay Vilas Samak, Tanmay Vilas Samak, Bing Li +1
Simulation-based design, optimization, and validation of autonomous vehicles have proven to be crucial for their improvement over the years. Nevertheless, the ultimate measure of e…
Digital Twins in the Cloud: A Modular, Scalable and Interoperable Framework for Accelerating Verification and Validation of Autonomous Driving Solutions
Tanmay Vilas Samak, Chinmay Vilas Samak, Giovanni Martino +2
Verification and validation (V&V) of autonomous vehicles (AVs) typically requires exhaustive testing across a variety of operating environments and driving scenarios including rare…
A Systematic Digital Engineering Approach to Verification & Validation of Autonomous Ground Vehicles in Off-Road Environments
Tanmay Vilas Samak, Chinmay Vilas Samak, Julia Brault +6
The engineering community currently encounters significant challenges in the systematic development and validation of autonomy algorithms for off-road ground vehicles. These challe…
Digital Twins Meet the Koopman Operator: Data-Driven Learning for Robust Autonomy
Chinmay Vilas Samak, Tanmay Vilas Samak, Ajinkya Joglekar +2
Contrary to on-road autonomous navigation, off-road autonomy is complicated by various factors ranging from sensing challenges to terrain variability. In such a milieu, data-driven…
Off-Road Autonomy Validation Using Scalable Digital Twin Simulations Within High-Performance Computing Clusters
Tanmay Vilas Samak, Chinmay Vilas Samak, Joey Binz +5
Off-road autonomy validation presents unique challenges due to the unpredictable and dynamic nature of off-road environments. Traditional methods focusing on sequentially sweeping…
Metaverse for Safer Roadways: An Immersive Digital Twin Framework for Exploring Human-Autonomy Coexistence in Urban Transportation Systems
Tanmay Vilas Samak, Chinmay Vilas Samak, Venkat Narayan Krovi
Societal-scale deployment of autonomous vehicles requires them to coexist with human drivers, necessitating mutual understanding and coordination among these entities. However, pur…
Mixed-Reality Digital Twins: Leveraging the Physical and Virtual Worlds for Hybrid Sim2Real Transition of Multi-Agent Reinforcement Learning Policies
Chinmay Vilas Samak, Tanmay Vilas Samak, Venkat Narayan Krovi
Multi-agent reinforcement learning (MARL) for cyber-physical vehicle systems usually requires a significantly long training time due to their inherent complexity. Furthermore, depl…
Autonomy Oriented Digital Twins for Real2Sim2Real Autoware Deployment
Chinmay Vilas Samak, Tanmay Vilas Samak
Modeling and simulation of autonomous vehicles plays a crucial role in achieving enterprise-scale realization that aligns with technical, business and regulatory requirements. Cont…
Towards Validation of Autonomous Vehicles Across Scales using an Integrated Digital Twin Framework
Tanmay Vilas Samak, Chinmay Vilas Samak, Venkat Narayan Krovi
Autonomous vehicle platforms of varying spatial scales are employed within the research and development spectrum based on space, safety and monetary constraints. However, deploying…
Nigel -- Mechatronic Design and Robust Sim2Real Control of an Over-Actuated Autonomous Vehicle
Chinmay Vilas Samak, Tanmay Vilas Samak, Javad Mohammadpour Velni +1
Simulation to reality (sim2real) transfer from a dynamics and controls perspective usually involves re-tuning or adapting the designed algorithms to suit real-world operating condi…
Multi-Agent Deep Reinforcement Learning for Cooperative and Competitive Autonomous Vehicles using AutoDRIVE Ecosystem
Tanmay Vilas Samak, Chinmay Vilas Samak, Venkat Krovi
This work presents a modular and parallelizable multi-agent deep reinforcement learning framework for imbibing cooperative as well as competitive behaviors within autonomous vehicl…
Towards Sim2Real Transfer of Autonomy Algorithms using AutoDRIVE Ecosystem
Chinmay Vilas Samak, Tanmay Vilas Samak, Venkat Krovi
The engineering community currently encounters significant challenges in the development of intelligent transportation algorithms that can be transferred from simulation to reality…
Towards Mechatronics Approach of System Design, Verification and Validation for Autonomous Vehicles
Chinmay Vilas Samak, Tanmay Vilas Samak, Venkat Krovi
Modern-day autonomous vehicles are increasingly becoming complex multidisciplinary systems composed of mechanical, electrical, electronic, computing and information sub-systems. Fu…
AutoDRIVE: A Comprehensive, Flexible and Integrated Digital Twin Ecosystem for Enhancing Autonomous Driving Research and Education
Tanmay Vilas Samak, Chinmay Vilas Samak, Sivanathan Kandhasamy +2
Prototyping and validating hardware-software components, sub-systems and systems within the intelligent transportation system-of-systems framework requires a modular yet flexible a…
AutoDRIVE -- Technical Report
Tanmay Vilas Samak, Chinmay Vilas Samak
This work presents AutoDRIVE, a comprehensive research and education platform for implementing and validating intelligent transportation algorithms pertaining to vehicular autonomy…
AutoDRIVE Simulator -- Technical Report
Tanmay Vilas Samak, Chinmay Vilas Samak
AutoDRIVE is envisioned to be a comprehensive research platform for scaled autonomous vehicles. This work is a stepping-stone towards the greater goal of realizing such a research…
Autonomous Racing using a Hybrid Imitation-Reinforcement Learning Architecture
Chinmay Vilas Samak, Tanmay Vilas Samak, Sivanathan Kandhasamy
In this work, we present a rigorous end-to-end control strategy for autonomous vehicles aimed at minimizing lap times in a time attack racing event. We also introduce AutoRACE Simu…
Proximally Optimal Predictive Control Algorithm for Path Tracking of Self-Driving Cars
Chinmay Vilas Samak, Tanmay Vilas Samak, Sivanathan Kandhasamy
This work presents proximally optimal predictive control algorithm, which is essentially a model-based lateral controller for steered autonomous vehicles that selects an optimal st…
AutoDRIVE Simulator: A Simulator for Scaled Autonomous Vehicle Research and Education
Tanmay Vilas Samak, Chinmay Vilas Samak, Ming Xie
AutoDRIVE is envisioned to be an integrated research and education platform for scaled autonomous vehicles and related applications. This work is a stepping-stone towards achieving…
Decentralized Motion Planning for Multi-Robot Navigation using Deep Reinforcement Learning
Sivanathan Kandhasamy, Vinayagam Babu Kuppusamy, Tanmay Vilas Samak +1
This work presents a decentralized motion planning framework for addressing the task of multi-robot navigation using deep reinforcement learning. A custom simulator was developed i…
Control Strategies for Autonomous Vehicles
Chinmay Vilas Samak, Tanmay Vilas Samak, Sivanathan Kandhasamy
This chapter focuses on the self-driving technology from a control perspective and investigates the control strategies used in autonomous vehicles and advanced driver-assistance sy…
Robust Behavioral Cloning for Autonomous Vehicles using End-to-End Imitation Learning
Tanmay Vilas Samak, Chinmay Vilas Samak, Sivanathan Kandhasamy
In this work, we present a lightweight pipeline for robust behavioral cloning of a human driver using end-to-end imitation learning. The proposed pipeline was employed to train and…