Stochastic Strategies for Robotic Surveillance as Stackelberg Games

随机监控Stackelberg博弈：防御部署与巡逻策略的协同优化

A Stochastic Surveillance Stackelberg Game: Co-Optimizing Defense Placement and Patrol Strategy

本文研究对抗环境下的随机巡逻Stackelberg博弈，引入节点异构防御并协同优化防御部署与巡逻策略，提出高效计算方法并验证其有效性。

Markov Chains with Maximum Return Time Entropy for Robotic Surveillance

Motivated by robotic surveillance applications, this paper studies the novel problem of maximizing the return time entropy of a Markov chain, subject to a graph topology with travel times and stationary distribution. The return time entropy is the weighted average, over all graph nodes, of the entropy of the first return times of the Markov chain; this objective function is a function series that does not admit in general a closed form. The paper features theoretical and computational contributions. First, we obtain a discrete-time delayed linear system for the return time probability distribu…

Markov Chain-Based Stochastic Strategies for Robotic Surveillance

This article surveys recent advancements of strategy designs for persistent robotic surveillance tasks with the focus on stochastic approaches. The problem describes how mobile robots stochastically patrol a graph in an efficient way where the efficiency is defined with respect to relevant underlying performance metrics. We first start by reviewing the basics of Markov chains, which is the primary motion model for stochastic robotic surveillance. Then two main criteria regarding the speed and unpredictability of surveillance strategies are discussed. The central objects that appear throughout …

RoSSO：基于JAX的高性能机器人监控策略优化Python包

RoSSO: A High-Performance Python Package for Robotic Surveillance Strategy Optimization Using JAX

本文提出基于JAX的Python包RoSSO，利用自动微分与约束参数化高效求解马尔可夫链优化问题，并引入贪心算法与多机器人扩展，通过旧金山警区实例验证其在机器人随机巡逻策略优化中的有效性。

Robotic Surveillance Based on the Meeting Time of Random Walks

This paper analyzes the meeting time between a pair of pursuer and evader performing random walks on digraphs. The existing bounds on the meeting time usually work only for certain classes of walks and cannot be used to formulate optimization problems and design robotic strategies. First, by analyzing multiple random walks on a common graph as a single random walk on the Kronecker product graph, we provide the first closed-form expression for the expected meeting time in terms of the transition matrices of the moving agents. This novel expression leads to necessary and sufficient conditions fo…

协作机器人分布式优化教程：从设置与算法到工具箱及研究方向

A Tutorial on Distributed Optimization for Cooperative Robotics: from Setups and Algorithms to Toolboxes and Research Directions

本文探讨了分布式优化在协作机器人中的应用，介绍了约束耦合和聚合优化框架，并展示了相关算法、工具箱及在异构机器人网络上的实验验证。