works on

From the 1 of 10 linked papers with an AI index.

activity
20242026
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10 papers

eess.SY2026

Control-Oriented System Identification: Classical, Learning, and Physics-Informed Approaches

S. Sivaranjani, Yuanyuan Shi, Nikolay Atanasov +6

The paper surveys classical, machine‑learning, and physics‑informed system identification methods that incorporate control‑relevant properties such as dissipativity and symmetry, d…

cs.RO2025

Learned IMU Bias Prediction for Invariant Visual Inertial Odometry

Abdullah Altawaitan, Jason Stanley, Sambaran Ghosal +2

Autonomous mobile robots operating in novel environments depend critically on accurate state estimation, often utilizing visual and inertial measurements. Recent work has shown tha…

cs.RO2025

SlideSLAM: Sparse, Lightweight, Decentralized Metric-Semantic SLAM for Multi-Robot Navigation

Xu Liu, Jiuzhou Lei, Ankit Prabhu +5

This paper develops a real-time decentralized metric-semantic SLAM algorithm that enables a heterogeneous robot team to collaboratively construct object-based metric-semantic maps.…

cs.RO2025

Physics-Informed Multi-Agent Reinforcement Learning for Distributed Multi-Robot Problems

Eduardo Sebastian, Thai Duong, Nikolay Atanasov +2

The networked nature of multi-robot systems presents challenges in the context of multi-agent reinforcement learning. Centralized control policies do not scale with increasing numb…

cs.RO2025

Control Strategies for Pursuit-Evasion Under Occlusion Using Visibility and Safety Barrier Functions

Minnan Zhou, Mustafa Shaikh, Vatsalya Chaubey +4

This paper develops a control strategy for pursuit-evasion problems in environments with occlusions. We address the challenge of a mobile pursuer keeping a mobile evader within its…

cs.MA2024

Distributed Multi-Agent Reinforcement Learning with One-hop Neighbors and Compute Straggler Mitigation

Baoqian Wang, Junfei Xie, Nikolay Atanasov

Most multi-agent reinforcement learning (MARL) methods are limited in the scale of problems they can handle. With increasing numbers of agents, the number of training iterations re…