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Safe Navigation on Path-Following Tasks: A Study of MPC-based Collision Avoidance Schemes in distributed robot systems

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JOURNAL OF INTELLIGENT & robotIC systems 2024年第4期110卷 1-17页

作者： Vangasse, Arthur da C. Freitas, Elias J. R. Raffo, Guilherme V. Pimenta, Luciano C. A. Univ Fed Minas Gerais UFMG Grad Program Elect Engn Ave Antonio Carlos 6627 BR-31270010 Belo Horizonte MG Brazil Fed Inst Minas Gerais IFMG Area Control & Automat R Mato Grosso02 BR-32407190 Ibirite MG Brazil Univ Fed Minas Gerais UFMG Dept Elect Engn Ave Antonio Carlos 6627 BR-31270901 Belo Horizonte MG Brazil

This work aims to enable distributed robot systems to follow time-varying paths safely. Artificial Vector Fields offer a viable alternative for addressing path-following challenges, yet collision avoidance among agents guided by such fields remains an open problem. To address this, we have designed a Model Predictive Control (MPC) setup that integrates an Artificial Vector Field reference with prominent collision avoidance methods, such as Optimal Reciprocal Collision Avoidance (ORCA) and Control Barrier Functions (CBF), to produce real-time, safe solutions. Our work involves a direct comparison between different MPC-based collision avoidance methods, and we have obtained results from various simulation scenarios as well as experiments on real robotic systems (Crazyflie 2.1). We aim to assess the applicability and limitations of these techniques through extracted metrics and insights.

关键词： Multi-robot systems Collision Avoidance distributed robot systems Model Predictive Control (MPC) Optimal Reciprocal Collision Avoidance (ORCA) Control Barrier Functions (CBF)

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Velocity Obstacle for Polytopic Collision Avoidance for distributed Multi-robot systems

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IEEE robotICS AND AUTOMATION LETTERS 2023年第6期8卷 3502-3509页

作者： Huang, Jihao Zeng, Jun Chi, Xuemin Sreenath, Koushil Liu, Zhitao Su, Hongye Zhejiang Univ Inst Cyber Syst & Control State Key Lab Ind Control Technol Hangzhou 310027 Peoples R China Univ Calif Berkeley Dept Mech Engn Hybrid Robot Grp Berkeley CA 94709 USA

Obstacle avoidance for multi-robot navigation with polytopic shapes is challenging. Existing works simplify the system dynamics or consider it as a convex or non-convex optimization problem with positive distance constraints between robots, which limits real-time performance and scalability. Additionally, generating collision-free behavior for polytopic-shaped robots is harder due to implicit and non-differentiable distance functions between polytopes. In this letter, we extend the concept of velocity obstacle (VO) principle for polytopic-shaped robots and propose a novel approach to construct the VO in the function of vertex coordinates and other robot's states. Compared with existing work about obstacle avoidance between polytopic-shaped robots, our approach is much more computationally efficient as the proposed approach for construction of VO between polytopes is optimization-free. Based on VO representation for polytopic shapes, we later propose a navigation approach for distributed multi-robot systems. We validate our proposed VO representation and navigation approach in multiple challenging scenarios including large-scale randomized tests, and our approach outperforms the state of art in many evaluation metrics, including completion rate, deadlock rate, and the average travel distance.

关键词： Collision avoidance robot kinematics Navigation Multi-robot systems Shape robot sensing systems Real-time systems distributed robot systems collision avoidance Index Terms multi-robot systems

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Priority-Based distributed Coordination for Heterogeneous Multi-robot systems With Realistic Assumptions

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IEEE robotICS AND AUTOMATION LETTERS 2021年第3期6卷 6131-6138页

作者： Cecchi, Michele Paiano, Matteo Mannucci, Anna Palleschi, Alessandro Pecora, Federico Pallottino, Lucia Univ Pisa Res Ctr E Piaggio Pisa Italy Univ Pisa Dipartimento Ingn Informaz Pisa Italy Orebro Univ Ctr Appl Autonomous Sensor Syst AASS Orebro Sweden

A standing challenge in current intralogistics is to reliably, effectively, yet safely coordinate large-scale, heterogeneous multi-robot fleets without posing constraints on the infrastructure or unrealistic assumptions on robots. A centralized approach, proposed by some of the authors in prior work, allows to overcome these limitations with medium-scale fleets (i.e., tens of robots). With the aim of scaling to hundreds of robots, in this article we explore a decentralized variant of the same approach. The proposed framework maintains the key features of the original approach, namely, ensuring safety despite uncertainties on robot motions, and generality with respect to robot platforms, motion planners and controllers. We include considerations on liveness and report solutions to prevent or recover from deadlocks in specific situations. We validate the approach empirically in simulation with large, heterogeneous multi-robot fleets (with up to 100 robots) operating in both benchmark and realistic environments.

关键词： distributed robot systems multi-robot systems planning scheduling and coordination

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distributed watchpoints: Debugging large modular robot systems

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INTERNATIONAL JOURNAL OF robotICS RESEARCH 2008年第3-4期27卷 315-329页

作者： De Rosa, Michael Goldstein, Seth Lee, Peter Campbell, Jason Pillai, Padmanabhan Carnegie Mellon Univ Dept Comp Sci Pittsburgh PA 15213 USA Intel Res Pittsburgh Pittsburgh PA 15213 USA

distributed systems frequently exhibit properties of interest which span multiple entities. These properties cannot easily be recognized from any single entity, but can be readily detected by combining the knowledge of multiple entities. Testing for distributed properties is especially important in debugging or verifying software for modular robots. We have developed a technique we call distributed watchpoint triggers which can efficiently recognize distributed conditions. Our watchpoint description language can handle a variety of temporal, spatial and logical properties spanning multiple robots. In this paper we present the specification language, describe the distributed online mechanism for detecting distributed conditions in a running system and evaluate the performance of our implementation.

关键词： cellular and modular robotics distributed robot systems programming environment

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Safety-Guaranteed distributed Formation Control of Multi-robot systems Over Graphs With Rigid and Elastic Edges

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IEEE robotICS AND AUTOMATION LETTERS 2024年第11期9卷 10240-10247页

作者： Pham, Hoang Ranasinghe, Nadun Le, Dong Atman, Made Widhi Surya Gusrialdi, Azwirman Tampere Univ Fac Engn & Nat Sci Tampere 33014 Finland

This letter considers the problem of formation control of multi-robot systems represented by a graph featuring both rigid and elastic edges, capturing specified range tolerance to the desired inter-robot distances. The objective is to navigate the robots safely through unknown environments with obstacles, utilizing onboard sensors like LiDAR while maintaining inter-robot distance constraints. To this end, a novel cooperative control algorithm is proposed, employing quadratic programming and leveraging control barrier functions to integrate multiple control objectives seamlessly. This approach ensures a unified strategy and provides a safety certificate. Experimental validation of the proposed cooperative control algorithm is conducted using a robotic testbed.

关键词： robots robot sensing systems robot kinematics Collision avoidance Sensors Formation control Multi-robot systems Mobile robots Safety Navigation distributed robot systems range sensing collision avoidance control barrier function formation control

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Adaptive-Resolution Cooperative Field Mapping With Event-Triggered distributed Map Fusion

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IEEE robotICS AND AUTOMATION LETTERS 2025年第2期10卷 1058-1065页

作者： Ding, Tianyi Zheng, Ronghao Zhang, Senlin Liu, Meiqin Zhejiang Univ Coll Elect Engn Hangzhou 310027 Peoples R China Zhejiang Univ Natl Key Lab Ind Control Technol Hangzhou 310027 Peoples R China Zhejiang Univ Jinhua Inst Jinhua 321036 Peoples R China Zhejiang Univ Natl Key Lab Ind Control Technol Hangzhou 310027 Peoples R China Xi An Jiao Tong Univ Natl Key Lab Human Machine Hybrid Augmented Intell Xian 710049 Peoples R China

Cooperative scalar field mapping is an important task for multi-robot systems. However, the limited communication and computation resources of robots have hindered the application of cooperative field mapping in large-scale scenarios. This letter proposes an adaptive-resolution Gaussian process mapping with event-triggered distributed map fusion to overcome these resource limitations. A novel event-triggered communication mechanism is proposed for distributed map fusion under range-limited communication. A resolution adaptation method is developed to balance the mapping computation, communication resources, and accuracy. A closed-form approximated information metric is derived for faster map resolution optimization. Finally, the performances of the proposed algorithms are validated by real online light field mapping experiments.

关键词： robots Event detection robot kinematics Multi-robot systems Kernel Gaussian processes robot sensing systems Optimization Measurement Light fields distributed robot systems mapping multi-robot systems

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Decentralized Density Control of Multi-robot systems Using PDE-Constrained Optimization

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IEEE robotICS AND AUTOMATION LETTERS 2025年第4期10卷 4045-4052页

作者： Niu, Longchen Notomista, Gennaro Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

In this letter, we propose a decentralized optimal density control strategy for multi-robot systems modeled as interacting Brownian particles. The robots' density dynamics are described by the Fokker-Planck equation, and an optimal control problem is formulated and solved accordingly. The stability of the decentralized controller is mathematically proven, and validated through simulations and experiments with a team of real brushbots. The results confirm the convergence of the proposed density-based decentralized optimal controller.

关键词： robots Mathematical models Noise robot sensing systems Stochastic processes Optimization Probability density function Location awareness Swarm robotics Convergence distributed robot systems multi-robot systems optimization and optimal control

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Swarm robotic Flocking With Aggregation Ability Privacy

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 10596-10608页

作者： Zhang, Shuai Huang, Yunke Li, Weizi Pan, Jia Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Univ Hong Kong TransGP Ctr Hong Kong Peoples R China Univ Tennessee Knoxville Min H Kao Dept Elect Engn & Comp Sci Knoxville TN 37996 USA

We address the challenge of achieving flocking behavior in swarm robotic systems without compromising the privacy of individual robots' aggregation capabilities. Traditional flocking algorithms are susceptible to privacy breaches, as adversaries can deduce the identity and aggregation abilities of robots by observing their movements. We introduce a novel control mechanism for privacy-preserving flocking, leveraging the Laplace mechanism within the framework of differential privacy. Our method mitigates privacy breaches by introducing a controlled level of noise, thus obscuring sensitive information. We explore the trade-off between privacy and utility by varying the differential privacy parameter & varepsilon;. Our quantitative analysis reveals that & varepsilon;<= 0.13 represents a lower threshold where private information is almost completely protected, whereas & varepsilon;>= 0.85 marks an upper threshold where private information cannot be protected at all. Empirical results validate that our approach effectively maintains privacy of the robots' aggregation abilities throughout the flocking process. Note to Practitioners-This paper was motivated by the problem of preserving privacy of individual robots in a swarm robotic system. Existing approaches to address this issue generally consider that accomplishing complex tasks requiring explicit information sharing between robots, while explicit communication in public channel carries the risk of information leakage. It is not always like this in real adversarial environments, and this assumption restricts the investigation of privacy in autonomous systems. This paper suggests that an individual robot can use its sensors onboard to perceive states of other neighbors in a distributed way without explicit communication. Despite avoiding information leakage during explicit information sharing between robots, the configuration of swarm can still reveal sensitive information about the ability of each robot. In this paper,

关键词： robots Privacy robot sensing systems Swarm robotics Differential privacy Target tracking Information leakage Information sharing Security Service robots distributed robot systems multi-robot systems swarm robotics

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Riemannian Optimization for Active Mapping With robot Teams

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IEEE TRANSACTIONS ON robotICS 2025年 41卷 1077-1097页

作者： Asgharivaskasi, Arash Girke, Fritz Atanasov, Nikolay Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA Tech Univ Munich Sch Computat Informat & Technol D-80333 Munich Germany

Autonomous exploration of unknown environments using a team of mobile robots demands distributed perception and planning strategies to enable efficient and scalable performance. Ideally, each robot should update its map and plan its motion not only relying on its own observations, but also considering the observations of its peers. Centralized solutions to multirobot coordination are susceptible to central node failure and require a sophisticated communication infrastructure for reliable operation. Current decentralized active mapping methods consider simplistic robot models with linear-Gaussian observations and Euclidean robot states. In this work, we present a distributed multirobot mapping and planning method, called Riemannian optimization for active mapping (ROAM). We formulate an optimization problem over a graph with node variables belonging to a Riemannian manifold and a consensus constraint requiring feasible solutions to agree on the node variables. We develop a distributed Riemannian optimization algorithm that relies only on one-hop communication to solve the problem with consensus and optimality guarantees. We show that multirobot active mapping can be achieved via two applications of our distributed Riemannian optimization over different manifolds: distributed estimation of a 3-D semantic map and distributed planning of SE(3) trajectories that minimize map uncertainty. We demonstrate the performance of ROAM in simulation and real-world experiments using a team of robots with RGB-D cameras.

关键词： robots robot kinematics Optimization robot sensing systems Planning Manifolds Semantics Trajectory Peer-to-peer computing Octrees distributed Riemannian optimization distributed robot systems mapping reactive and sensor-based planning

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distributed Multirobot Multitarget Tracking Using Heterogeneous Limited-Range Sensors

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IEEE TRANSACTIONS ON robotICS 2025年 41卷 1755-1772页

作者： Chen, Jun Abugurain, Mohammed Dames, Philip Park, Shinkyu Nanjing Normal Univ Sch Elect & Automat Engn Nanjing 210023 Peoples R China Jiangsu Key Lab Addit Mfg Equipment Technol Nanjing 210023 Peoples R China King Abdullah Univ Sci & Technol Comp Elect & Math Sci & Engn Div Thuwal 23955 Saudi Arabia Temple Univ Dept Mech Engn Philadelphia PA 19122 USA

Utilizing heterogeneous mobile sensors to actively gather information improves adaptability and reliability in extended environments. This article presents a cooperative multirobot multitarget search and tracking framework aimed at enhancing the efficiency of the heterogeneous sensor network, and consequently, improving the overall target tracking accuracy. The concept of normalized unused sensing capacity is introduced to quantify the information a sensor is currently gathering relative to its theoretical maximum. This measurement can be computed using entirely local information and is applicable to various sensor models, distinguishing it from previous literature on the subject. It is then utilized to develop a heuristics distributed coverage control strategy for a heterogeneous sensor network, adaptively balancing the workload based on each sensor's current unused capacity. The algorithm is validated through a series of robot operating system (ROS) and MATLAB simulations, demonstrating superior results compared to standard approaches that do not account for heterogeneity or current usage rates.

关键词： distributed robot systems multirobot systems networked robots reactive and sensor-based planning distributed robot systems multirobot systems networked robots reactive and sensor-based planning

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