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Robust Estimation and Control for Heterogeneous Multi-agent Systems Based on Decentralized k-hop Prescribed Performance Observers
Tommaso Zaccherini, Siyuan Liu, Dimos V. Dimarogonas
We propose decentralized k-hop Prescribed Performance State and Input Observers for heterogeneous multi-agent systems subject to bounded external disturbances. In the proposed inpu…
Correct-by-Design Control Synthesis of Stochastic Multi-agent Systems: a Robust Tensor-based Solution
Ruohan Wang, Siyuan Liu, Zhiyong Sun +1
Discrete-time stochastic systems with continuous spaces are hard to verify and control, even with MDP abstractions due to the curse of dimensionality. We propose an abstraction-bas…
Sampling-Based Planning Under STL Specifications: A Forward Invariance Approach
Gregorio Marchesini, Siyuan Liu, Lars Lindemann +1
We propose a variant of the Rapidly Exploring Random Tree Star (RRT) algorithm to synthesize trajectories satisfying a given spatio-temporal specification expressed in a…
UTTG_ A Universal Teleoperation Approach via Online Trajectory Generation
Shengjian Fang, Yixuan Zhou, Yu Zheng +3
Teleoperation is crucial for hazardous environment operations and serves as a key tool for collecting expert demonstrations in robot learning. However, existing methods face roboti…
Communication-aware Multi-agent Systems Control Based on -hop Distributed Observers
Tommaso Zaccherini, Siyuan Liu, Dimos V. Dimarogonas
We propose a distributed control strategy to allow the control of a multi-agent system requiring k-hop interactions based on the design of distributed state and input observers. In…