3 citations · 5 across the 13 of their papers we have counts for
6 papers · 1 filter
ContractionPPO: Certified Reinforcement Learning via Differentiable Contraction Layers
Vrushabh Zinage, Narek Harutyunyan, Eric Verheyden +2
Legged locomotion in unstructured environments demands not only high-performance control policies but also formal guarantees to ensure robustness under perturbations. Control metho…
Transformer-Based Model Predictive Path Integral Control
Shrenik Zinage, Vrushabh Zinage, Efstathios Bakolas
This paper presents a novel approach to improve the Model Predictive Path Integral (MPPI) control by using a transformer to initialize the mean control sequence. Traditional MPPI m…
Fast End-to-End Generation of Belief Space Paths for Minimum Sensing Navigation
Lukas Taus, Vrushabh Zinage, Takashi Tanaka +1
We revisit the problem of motion planning in the Gaussian belief space. Motivated by the fact that most existing sampling-based planners suffer from high computational costs due to…
Decentralized Safe and Scalable Multi-Agent Control under Limited Actuation
Vrushabh Zinage, Abhishek Jha, Rohan Chandra +1
To deploy safe and agile robots in cluttered environments, there is a need to develop fully decentralized controllers that guarantee safety, respect actuation limits, prevent deadl…
TransformerMPC: Accelerating Model Predictive Control via Transformers
Vrushabh Zinage, Ahmed Khalil, Efstathios Bakolas
In this paper, we address the problem of reducing the computational burden of Model Predictive Control (MPC) for real-time robotic applications. We propose TransformerMPC, a method…
Mathematical Properties of Generalized Shape Expansion-Based Motion Planning Algorithms
Adhvaith Ramkumar, Vrushabh Zinage, Satadal Ghosh
Motion planning is an essential aspect of autonomous systems and robotics and is an active area of research. A recently-proposed sampling-based motion planning algorithm, termed 'G…