202 citations · 563 across the 65 of their papers we have counts for
7 papers · 1 filter
Learning to Identify Graphs from Node Trajectories in Multi-Robot Networks
Eduardo Sebastian, Thai Duong, Nikolay Atanasov +2
The graph identification problem consists of discovering the interactions among nodes in a network given their state/feature trajectories. This problem is challenging because the b…
LEMURS: Learning Distributed Multi-Robot Interactions
Eduardo Sebastian, Thai Duong, Nikolay Atanasov +2
This paper presents LEMURS, an algorithm for learning scalable multi-robot control policies from cooperative task demonstrations. We propose a port-Hamiltonian description of the m…
Control Barriers in Bayesian Learning of System Dynamics
Vikas Dhiman, Mohammad Javad Khojasteh, Massimo Franceschetti +1
This paper focuses on learning a model of system dynamics online while satisfying safety constraints. Our objective is to avoid offline system identification or hand-specified mode…
Safe Robot Navigation in Cluttered Environments using Invariant Ellipsoids and a Reference Governor
Zhichao Li, Thai Duong, Nikolay Atanasov
This paper considers the problem of safe autonomous navigation in unknown environments, relying on local obstacle sensing. We consider a control-affine nonlinear robot system subje…
Scheduling Nonlinear Sensors for Stochastic Process Estimation
Vasileios Tzoumas, Nikolay A. Atanasov, Ali Jadbabaie +1
In this paper, we focus on activating only a few sensors, among many available, to estimate the state of a stochastic process of interest. This problem is important in applications…
Myopic Policy Bounds for Information Acquisition POMDPs
Mikko Lauri, Nikolay Atanasov, George J. Pappas +1
This paper addresses the problem of optimal control of robotic sensing systems aimed at autonomous information gathering in scenarios such as environmental monitoring, search and r…
Information Acquisition with Sensing Robots: Algorithms and Error Bounds
Nikolay Atanasov, Jerome Le Ny, Kostas Daniilidis +1
Utilizing the capabilities of configurable sensing systems requires addressing difficult information gathering problems. Near-optimal approaches exist for sensing systems without i…