activity
20232026
most citedBenchmarking Model Predictive Control Algorithms in Building Optimization Testing Framework (BOPTEST)

5 citations · 5 across the 4 of their papers we have counts for

collaborators

7 papers

cs.RO2026

DuoMind: Enabling Distributed Multi-Robot Coordination with Semantic Communication

Hanchu Zhou, Dechen Gao, Hang Wang +5

Vision-language models (VLMs) and vision-language-action models (VLAs) have recently driven rapid progress in general-purpose robots, yet most progress has focused on single-robot…

cs.RO2026

Agile-WAM: An Agile Tactile World Action Model for Contact-Rich Robot Control

Hanchu Zhou, Brendan Lynch, Raman Goyal +4

World Action Models (WAMs) advance beyond conventional visuomotor policies by jointly predicting future world states and robot actions, enabling the policy to learn phys- ical dyna…

cs.LG2026

A Machine Learning Framework for Fault Detection, Isolation, and Severity Prediction of Autonomous VTOL Aircraft

Ripon C. Sarker, Pedram H. Dabaghian, Raman Goyal +1

Fault detection in autonomous VTOL aircraft is critical because even minor component degradations can rapidly destabilize multirotor vehicles operating in complex, safety-critical…

cs.RO2026

Industrial Dexterity Benchmark: A Hardware-Software Benchmarking Platform for Industrial Dexterous Manipulation

Honglu He, Jacob Laufer, Zhiwu Zheng +8

Dexterous manipulation remains a critical bottleneck in industrial automation; tasks such as cable routing, connector insertion, and precision assembly still rely heavily on manual…

math.OC2024

An Optimal Solution to Infinite Horizon Nonholonomic and Discounted Nonlinear Control Problems

Mohamed Naveed Gul Mohamed, Abhijeet, Aayushman Sharma +2

This paper considers the infinite horizon optimal control problem for nonlinear systems. Under the condition of nonlinear controllability of the system to any terminal set containi…

cs.RO2023

Learning to Control under Uncertainty with Data-Based Iterative Linear Quadratic Regulator

Ran Wang, Raman Goyal, Suman Chakravorty

This paper studies the learning-to-control problem under process and sensing uncertainties for dynamical systems. In our previous work, we developed a data-based generalization of…

eess.SY2023★ 5 cited

Benchmarking Model Predictive Control Algorithms in Building Optimization Testing Framework (BOPTEST)

Saman Mostafavi, Chihyeon Song, Aayushman Sharma +2

We present a data-driven modeling and control framework for physics-based building emulators. Our approach consists of: (a) Offline training of differentiable surrogate models that…