Nikolay Atanasov

Assistant Professor

University of California, San Diego

United States

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Dr. Nikolay Atanasov is an Assistant Professor at the University of California, San Diego. His research areas encompass multi-object tracking, robot navigation, reinforcement learning, and distributed estimation in sensor networks. He has contributed to the field with recent publications on topics such as probabilistic data association, safe robot navigation, and variational inference. Dr. Atanasov's work aims to advance the capabilities of robotic systems through innovative computational methods.

Articles (20)

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Collaborators (8)

George Pappas

Professor

University of Pennsylvania

UNITED STATES

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Mohammad Javad Khojasteh

Gleason Endowed Assistant Professor

Rochester Institute of Technology

UNITED STATES

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Jonathan How

Massachusetts Institute of Technology

UNITED STATES

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José A. Castellanos

Universidad de Zaragoza

SPAIN

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Sonia Martinez

Professor

University of California, San Diego

UNITED STATES

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Melvin Leok

Professor

University of California, San Diego

UNITED STATES

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Shumon Koga

Associate Professor

Kobe University

JAPAN

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Florian Meyer

University of California, San Diego

UNITED STATES

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Nikolay Atanasov

Research Interests

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Articles (20)

Importance Sampling With Stochastic Particle Flow and Diffusion Optimization

Distributed Bayesian Estimation in Sensor Networks: Consensus on Marginal Densities

Distributed Variational Inference for Online Supervised Learning

PKF: Probabilistic Data Association Kalman Filter for Multi-Object Tracking

Sensor-based distributionally robust control for safe robot navigation in dynamic environments

Continuity and Boundedness of Minimum-Norm CBF-Safe Controllers

Distributed Multiagent Reinforcement Learning With One-Hop Neighbors and Compute Straggler Mitigation

Variable-Frequency Model Learning and Predictive Control for Jumping Maneuvers on Legged Robots

Physics-Informed Multiagent Reinforcement Learning for Distributed Multirobot Problems

Riemannian Optimization for Active Mapping With Robot Teams

Energy-Aware, Collision-Free Information Gathering for Heterogeneous Robot Teams

A Survey on Active Simultaneous Localization and Mapping: State of the Art and New Frontiers

Control Barriers in Bayesian Learning of System Dynamics

Control Synthesis for Stability and Safety by Differential Complementarity Problem

Semantic OcTree Mapping and Shannon Mutual Information Computation for Robot Exploration

Distributed Bayesian Estimation of Continuous Variables Over Time-Varying Directed Networks

Autonomous Navigation in Unknown Environments With Sparse Bayesian Kernel-Based Occupancy Mapping

Dense Incremental Metric-Semantic Mapping for Multiagent Systems via Sparse Gaussian Process Regression

Safe Control Synthesis With Uncertain Dynamics and Constraints

Adaptive Control of SE(3) Hamiltonian Dynamics With Learned Disturbance Features

Collaborators (8)

George Pappas

Mohammad Javad Khojasteh

Jonathan How

José A. Castellanos

Sonia Martinez

Melvin Leok

Shumon Koga

Florian Meyer

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