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Controller synthesis is a theoretical approach to the systematic design of discrete event systems. It constructs a controller to provide feedback and control to the system, ensuring it meets specified control specifications. Traditional…

多智能体系统 · 计算机科学 2025-09-03 Ruohan Huang , Zining Cao

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 approaches often lack the guarantee on correctness and…

机器人学 · 计算机科学 2024-04-10 Zesen Liu , Meng Guo , Weimin Bao , Zhongkui Li

Collaborative robotics cells leverage heterogeneous agents to provide agile production solutions. Effective coordination is essential to prevent inefficiencies and risks for human operators working alongside robots. This paper proposes a…

机器人学 · 计算机科学 2025-03-11 Samuele Sandrini , Marco Faroni , Nicola Pedrocchi

This paper investigates the problem of designing control policies that satisfy high-level specifications described by signal temporal logic (STL) in unknown, stochastic environments. While many existing works concentrate on optimizing the…

系统与控制 · 电气工程与系统科学 2024-12-16 Siqi Wang , Shaoyuan Li , Li Yin , Xiang Yin

With a growing complexity of the intelligent traffic system (ITS), an integrated control of ITS that is capable of considering plentiful heterogeneous intelligent agents is desired. However, existing control methods based on the centralized…

系统与控制 · 电气工程与系统科学 2023-08-09 Shengyue Yao , Jingru Yu , Yi Yu , Jia Xu , Xingyuan Dai , Honghai Li , Fei-Yue Wang , Yilun Lin

We propose novel techniques for task allocation and planning in multi-robot systems operating in uncertain environments. Task allocation is performed simultaneously with planning, which provides more detailed information about individual…

人工智能 · 计算机科学 2018-08-13 Fatma Faruq , Bruno Lacerda , Nick Hawes , David Parker

Multi-objective combinatorial optimization seeks Pareto-optimal solutions over exponentially large discrete spaces, yet existing methods sacrifice generality, scalability, or theoretical guarantees. We reformulate it as an online learning…

机器学习 · 计算机科学 2026-02-13 Esha Singh , Dongxia Wu , Chien-Yi Yang , Tajana Rosing , Rose Yu , Yi-An Ma

Balancing safety, efficiency, and interaction is fundamental to designing autonomous driving agents and to understanding autonomous vehicle (AV) behavior in real-world operation. This study introduces an empirical learning framework that…

机器人学 · 计算机科学 2026-01-28 Mohammad Elayan , Wissam Kontar

We consider the problem of controlling a heterogeneous multi-agent system required to satisfy temporal logic requirements. Capability Temporal Logic (CaTL) was recently proposed to formalize such specifications for deploying a team of…

系统与控制 · 电气工程与系统科学 2023-04-14 Wenliang Liu , Kevin Leahy , Zachary Serlin , Calin Belta

We present a shared control paradigm that improves a user's ability to operate complex, dynamic systems in potentially dangerous environments without a priori knowledge of the user's objective. In this paradigm, the role of the autonomous…

机器人学 · 计算机科学 2019-06-07 Alexander Broad , Todd Murphey , Brenna Argall

Shared autonomy methods, where a human operator and a robot arm work together, have enabled robots to complete a range of complex and highly variable tasks. Existing work primarily focuses on one human sharing autonomy with a single robot.…

In this paper, we aim to achieve a human-robot work balance by implementing shared autonomy through a web interface. Shared autonomy integrates user input with the autonomous capabilities of the robot and therefore increases the overall…

机器人学 · 计算机科学 2020-02-21 Yug Ajmera , Arshad Javed

This paper connects discrete optimal transport to a certain class of multi-objective optimization problems. In both settings, the decision variables can be organized into a matrix. In the multi-objective problem, the notion of Pareto…

最优化与控制 · 数学 2017-12-04 Johannes M. Schumacher

In this work, we propose a novel shared autonomy framework to operate articulated robots. We provide strategies to design both the task-oriented hierarchical planning and policy shaping algorithms for efficient human-robot interactions in…

机器人学 · 计算机科学 2023-07-06 Ehsan Yousefi , Mo Chen , Inna Sharf

In hierarchical planning for Markov decision processes (MDPs), temporal abstraction allows planning with macro-actions that take place at different time scale in form of sequential composition. In this paper, we propose a novel approach to…

最优化与控制 · 数学 2019-07-24 Xuan Liu , Jie Fu

Motivated by a plethora of practical examples where bias is induced by automated-decision making algorithms, there has been strong recent interest in the design of fair algorithms. However, there is often a dichotomy between fairness and…

人工智能 · 计算机科学 2023-07-13 April Niu , Agnes Totschnig , Adrian Vetta

Autonomous navigation often requires the simultaneous optimization of multiple objectives. The most common approach scalarizes these into a single cost function using a weighted sum, but this method is unable to find all possible trade-offs…

机器人学 · 计算机科学 2026-04-07 Krishna Kalavadia , Shamak Dutta , Yash Vardhan Pant , Stephen L. Smith

This paper considers the scheduling of stochastic jobs on parallel identical machines to minimize the expected total weighted completion time. While this is a classical problem with a significant body of research on approximation algorithms…

数据结构与算法 · 计算机科学 2026-01-27 Benjamin Moseley , Kirk Pruhs , Marc Uetz , Rudy Zhou

The resource management of a phase array system capable of multiple target tracking and surveillance is critical for the realization of its full potential. Present work aims to improve the performance of an existing method, time-balance…

信号处理 · 电气工程与系统科学 2025-12-03 Ömer Çayır , Çağatay Candan

In this paper, we consider the problem of allocating human operator assistance in a system with multiple autonomous robots. Each robot is required to complete independent missions, each defined as a sequence of tasks. While executing a…

机器人学 · 计算机科学 2022-09-09 Yifan Cai , Abhinav Dahiya , Nils Wilde , Stephen L. Smith