6 papers
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…
Disturbance Observer-based Robust Integral Control Barrier Functions for Nonlinear Systems with High Relative Degree
Vrushabh Zinage, Rohan Chandra, Efstathios Bakolas
In this paper, we consider the problem of safe control synthesis of general controlled nonlinear systems in the presence of bounded additive disturbances. Towards this aim, we firs…
Optimal Sampling-based Motion Planning in Gaussian Belief Space for Minimum Sensing Navigation
Vrushabh Zinage, Ali Reza Pedram, Takashi Tanaka
In this paper, we consider the motion planning problem in Gaussian belief space for minimum sensing navigation. Despite the extensive use of sampling-based algorithms and their rig…
Neural Koopman Lyapunov Control
Vrushabh Zinage, Efstathios Bakolas
Learning and synthesizing stabilizing controllers for unknown nonlinear control systems is a challenging problem for real-world and industrial applications. Koopman operator theory…