23 citations · 31 across the 19 of their papers we have counts for
20 papers
UMBRELLA: Uncertainty-aware Multi-robot Reactive Coordination under Dynamic Temporal Logic Tasks
Qisheng Zhao, Meng Guo, Hengxuan Du +2
Multi-robot systems can be extremely efficient for accomplishing team-wise tasks by acting concurrently and collaboratively. However, most existing methods either assume static tas…
Multi-UAV Deployment in Obstacle-Cluttered Environments with LOS Connectivity
Yuda Chen, Shuaikang Wang, Jie Li +1
A reliable communication network is essential for multiple UAVs operating within obstacle-cluttered environments, where limited communication due to obstructions often occurs. A co…
Multi-agent Coordination Under Temporal Logic Tasks and Team-Wise Intermittent Communication
Junjie Wang, Meng Guo, Zhongkui Li
Multi-agent systems outperform single agent in complex collaborative tasks. However, in large-scale scenarios, ensuring timely information exchange during decentralized task execut…
Multi-UAV Deployment in Obstacle-Cluttered Environments with LOS Connectivity
Yuda Chen, Meng Guo
A reliable communication network is essential for multiple UAVs operating within obstacle-cluttered environments, where limited communication due to obstructions often occurs. A co…
Fast and Adaptive Multi-agent Planning under Collaborative Temporal Logic Tasks via Poset Products
Zesen Liu, Meng Guo, Weimin Bao +1
Efficient coordination and planning is essential for large-scale multi-agent systems that collaborate in a shared dynamic environment. Heuristic search methods or learning-based ap…
Hybrid and Oriented Harmonic Potentials for Safe Task Execution in Unknown Environment
Shuaikang Wang, Meng Guo
Harmonic potentials provide globally convergent potential fields that are provably free of local minima. Due to its analytical format, it is particularly suitable for generating sa…
Combinatorial-hybrid Optimization for Multi-agent Systems under Collaborative Tasks
Zili Tang, Junfeng Chen, Meng Guo
Multi-agent systems can be extremely efficient when working concurrently and collaboratively, e.g., for transportation, maintenance, search and rescue. Coordination of such teams o…
Hierarchical Motion Planning under Probabilistic Temporal Tasks and Safe-Return Constraints
Meng Guo, Tianjun Liao, Junjie Wang +1
Safety is crucial for robotic missions within an uncertain environment. Common safety requirements such as collision avoidance are only state-dependent, which can be restrictive fo…
Online Planning of Uncertain MDPs under Temporal Tasks and Safe-Return Constraints
Yuyang Zhang, Meng Guo
This paper addresses the online motion planning problem of mobile robots under complex high-level tasks. The robot motion is modeled as an uncertain Markov Decision Process (MDP) d…
Time Minimization and Online Synchronization for Multi-agent Systems under Collaborative Temporal Tasks
Zesen Liu, Meng Guo, Zhongkui Li
Multi-agent systems can be extremely efficient when solving a team-wide task in a concurrent manner. However, without proper synchronization, the correctness of the combined behavi…
Interactive Human-in-the-loop Coordination of Manipulation Skills Learned from Demonstration
Meng Guo, Mathias Buerger
Learning from demonstration (LfD) provides a fast, intuitive and efficient framework to program robot skills, which has gained growing interest both in research and industrial appl…
Deadlock Resolution and Recursive Feasibility in MPC-based Multi-robot Trajectory Generation
Yuda Chen, Meng Guo, Zhongkui Li
Online collision-free trajectory generation within a shared workspace is fundamental for most multi-robot applications. However, many widely-used methods based on model predictive…
Geometric Task Networks: Learning Efficient and Explainable Skill Coordination for Object Manipulation
Meng Guo, Mathias Bürger
Complex manipulation tasks can contain various execution branches of primitive skills in sequence or in parallel under different scenarios. Manual specifications of such branching…
Learning and Sequencing of Object-Centric Manipulation Skills for Industrial Tasks
Leonel Rozo, Meng Guo, Andras G. Kupcsik +8
Enabling robots to quickly learn manipulation skills is an important, yet challenging problem. Such manipulation skills should be flexible, e.g., be able adapt to the current works…
Human-in-the-Loop Mixed-Initiative Control under Temporal Tasks
Meng Guo, Sofie Andersson, Dimos V. Dimarogonas
This paper considers the motion control and task planning problem of mobile robots under complex high-level tasks and human initiatives. The assigned task is specified as Linear Te…
Probabilistic Motion Planning under Temporal Tasks and Soft Constraints
Meng Guo, Michael M. Zavlanos
This paper studies motion planning of a mobile robot under uncertainty. The control objective is to synthesize a {finite-memory} control policy, such that a high-level task specifi…
Multi-Robot Data Gathering Under Buffer Constraints and Intermittent Communication
Meng Guo, Michael M. Zavlanos
We consider a team of heterogeneous robots which are deployed within a common workspace to gather different types of data. The robots have different roles due to different capabili…
Temporal Logic Task Planning and Intermittent Connectivity Control of Mobile Robot Networks
Yiannis Kantaros, Meng Guo, Michael M. Zavlanos
In this paper, we develop a distributed intermittent communication and task planning framework for mobile robot teams. The goal of the robots is to accomplish complex tasks, captur…
Communication-Free Multi-Agent Control under Local Temporal Tasks and Relative-Distance Constraints
Meng Guo, Jana Tumova, Dimos V. Dimarogonas
We propose a distributed control and coordination strategy for multi-agent systems where each agent has a local task specified as a Linear Temporal Logic (LTL) formula and at the s…
Cooperative Decentralized Multi-agent Control under Local LTL Tasks and Connectivity Constraints
Meng Guo, Jana Tumova, Dimos V. Dimarogonas
We propose a framework for the decentralized control of a team of agents that are assigned local tasks expressed as Linear Temporal Logic (LTL) formulas. Each local LTL task specif…