9 citations · 16 across the 12 of their papers we have counts for
13 papers
Physics constrained learning of stochastic characteristics
Pardha Sai Krishna Ala, Ameya Salvi, Venkat Krovi +1
Accurate state estimation requires careful consideration of uncertainty surrounding the process and measurement models; these characteristics are usually not well-known and need an…
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…
Characterizing gaussian mixture of motion modes for skid-steer vehicle state estimation
Ameya Salvi, Mark Brudnak, Jonathon M. Smereka +2
Skid-steered wheel mobile robots (SSWMRs) are characterized by the unique domination of the tire-terrain skidding for the robot to move. The lack of reliable friction models cascad…
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…
Online identification of skidding modes with interactive multiple model estimation
Ameya Salvi, Pardha Sai Krishna Ala, Jonathon M. Smereka +4
Skid-steered wheel mobile robots (SSWMRs) operate in a variety of outdoor environments exhibiting motion behaviors dominated by the effects of complex wheel-ground interactions. Ch…
Stabilization of vertical motion of a vehicle on bumpy terrain using deep reinforcement learning
Ameya Salvi, John Coleman, Jake Buzhardt +2
Stabilizing vertical dynamics for on-road and off-road vehicles is an important research area that has been looked at mostly from the point of view of ride comfort. The advent of a…
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…
An Overview of Automated Vehicle Longitudinal Platoon Formation Strategies
M Sabbir Salek, Mugdha Basu Thakur, Pardha Sai Krishna Ala +5
Automated vehicle (AV) platooning has the potential to improve the safety, operational, and energy efficiency of surface transportation systems by limiting or eliminating human inv…
Contrastive Representation Disentanglement for Clustering
Fei Ding, Dan Zhang, Yin Yang +2
Clustering continues to be a significant and challenging task. Recent studies have demonstrated impressive results by applying clustering to feature representations acquired throug…
Multi-level Knowledge Distillation via Knowledge Alignment and Correlation
Fei Ding, Yin Yang, Hongxin Hu +2
Knowledge distillation (KD) has become an important technique for model compression and knowledge transfer. In this work, we first perform a comprehensive analysis of the knowledge…