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Koord: A Language for Programming and Verifying distributed robotics Application

PROCEEDINGS OF THE ACM ON PROGRAMMING LANGUAGES-PACMPL 2020年第OOPSLA期4卷 1–30页

作者： Ghosh, Ritwika Hsieh, Chiao Misailovic, Sasa Mitra, Sayan Univ Illinois Urbana IL 61801 USA

A robot's code needs to sense the environment, control the hardware, and communicate with other robots. Current programming languages do not provide suitable abstractions that are independent of hardware platforms. Currently, developing robot applications requires detailed knowledge of signal processing, control, path planning, network protocols, and various platform-specific details. Further, porting applications across hardware platforms remains tedious. We present Koord a domain specific language for distributed robotics which abstracts platform-specific functions for sensing, communication, and low-level control. Koord makes the platform-independent control and coordination code portable and modularly verifiable. Koord raises the level of abstraction in programming by providing distributed shared memory for coordination and port interfaces for sensing and control. We have developed the formal executable semantics of Koord in the K framework. With this symbolic execution engine, we can identify assumptions (proof obligations) needed for gaining high assurance from Koord applications. We illustrate the power of Koord through three applications: formation flight, distributed delivery, and distributed mapping. We also use the three applications to demonstrate how platform-independent proof obligations can be discharged using the Koord Prover while platform-specific proof obligations can be checked by verifying the obligations using physics-based models and hybrid verification tools.

关键词： distributed robotics Programming Language for robotics

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Solving the task variant allocation problem in distributed robotics

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AUTONOMOUS ROBOTS 2018年第7期42卷 1477-1495页

作者： Cano, Jose White, David R. Bordallo, Alejandro McCreesh, Ciaran Michala, Anna Lito Singer, Jeremy Nagarajan, Vijay Univ Edinburgh Sch Informat Edinburgh EH8 9AB Midlothian Scotland Univ Glasgow Sch Comp Sci Glasgow G12 8RZ Lanark Scotland UCL Dept Comp Sci London WC1E 6BT England

We consider the problem of assigning software processes (or tasks) to hardware processors in distributed robotics environments. We introduce the notion of a task variant, which supports the adaptation of software to specific hardware configurations. Task variants facilitate the trade-off of functional quality versus the requisite capacity and type of target execution processors. We formalise the problem of assigning task variants to processors as a mathematical model that incorporates typical constraints found in robotics applications;the model is a constrained form of a multi-objective, multi-dimensional, multiple-choice knapsack problem. We propose and evaluate three different solution methods to the problem: constraint programming, a constructive greedy heuristic and a local search metaheuristic. Furthermore, we demonstrate the use of task variants in a real instance of a distributed interactive multi-agent navigation system, showing that our best solution method (constraint programming) improves the system's quality of service, as compared to the local search metaheuristic, the greedy heuristic and a randomised solution, by an average of 16, 31 and 56% respectively.

关键词： Task allocation distributed robotics Multi-robot systems Multi-objective optimisation

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DRONA: A Framework for Safe distributed Mobile robotics 17

DRONA: A Framework for Safe Distributed Mobile Robotics

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8th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS) held as part of Cyber-Physical Systems Week

作者： Desai, Ankush Saha, Indranil Yang, Jianqiao Qadeer, Shaz Seshia, Sanjit A. Univ Calif Berkeley Berkeley CA 94720 USA Indian Inst Technol Kanpur Uttar Pradesh India Microsoft Res Redmond WA USA

ISBN: (纸本)9781450349659

distributed mobile robotics (DMR) involves teams of networked robots navigating in a physical space to achieve tasks in a coordinated fashion. A major challenge in DMR is to program the ensemble of robots with formal guarantees and high assurance of correct operation. To this end, we introduce DRONA, a framework for building reliable DMR applications. This paper makes three central contributions: (1) We present a novel and provably correct decentralized asynchronous motion planner that can perform on-the-fly collision-free planning for dynamically generated tasks. Moreover, the motion planner is the first to take into account the fact that distributed robots may have clocks that are only synchronized up to a tolerance, i.e., they are almost synchronous;(2) We formalize the DMR system as a mixed-synchronous system, and present a sound abstraction-based verification approach for DMR systems, and (3) DRONA provides a state-machine based language for safe event-driven programming of a DMR system and the code generated by the compiler can be executed on platforms such as the robot operating system (ROS). To demonstrate the efficacy of DRONA, we build and verify a priority mail delivery system. Using our abstraction-based verification approach we were able to find, within a few minutes, bugs which could not be found by performing random simulation for several hours. Our verified decentralized motion-planner scales efficiently for large number of robots (upto 128 robots) and workspace sizes (upto a 256x256 grid).

关键词： distributed robotics Verification Programming Language for robotics Safe Mobile robotics Multi-Robot Motion Planning

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Edge Accelerated Robot Navigation With Collaborative Motion Planning

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2025年第2期30卷 1166-1178页

作者： Li, Guoliang Han, Ruihua Wang, Shuai Gao, Fei Eldar, Yonina C. Xu, Chengzhong Univ Macau Dept Comp & Informat Sci State Key Lab Internet Things Smart City SKL IOTSC Macau 999078 Peoples R China Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen 518055 Peoples R China Zhejiang Univ State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China Zhejiang Univ Huzhou Inst Hangzhou 310027 Zhejiang Peoples R China Weizmann Inst Sci Fac Math & Comp Sci IL-7610001 Rehovot Israel

Low-cost distributed robots suffer from limited onboard computing power, resulting in excessive computation time when navigating in cluttered environments. This article presents Edge Accelerated Robot Navigation (EARN), to achieve real-time collision avoidance by adopting collaborative motion planning. As such, each robot can dynamically switch between a conservative motion planner executed locally to guarantee safety (e.g., path-following) and an aggressive motion planner executed nonlocally to guarantee efficiency (e.g., overtaking). In contrast to existing motion planning approaches that ignore the interdependency between low-level motion planning and high-level resource allocation, EARN adopts model predictive switching (MPS) that maximizes the expected switching gain with respect to robot states and actions under computation and communication resource constraints. The MPS problem is solved by a tightly coupled decision making and motion planning framework based on bilevel mixed-integer nonlinear programming and penalty dual decomposition. We validate the performance of EARN in indoor simulation, outdoor simulation, and real-world environments. Experiments show that EARN achieves significantly smaller navigation time and higher success rates than state-of-the-art navigation approaches.

关键词： Collaborative computing distributed robotics model predictive switching (MPS) motion planning Collaborative computing distributed robotics model predictive switching (MPS) motion planning

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Autonomous ecologies of construction: Collaborative modular robotic material eco-systems with deep multi-agent reinforcement learning

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INTERNATIONAL JOURNAL OF ARCHITECTURAL COMPUTING 2024年第4期22卷 661-688页

作者： Hosmer, Tyson Mutis, Sergio Gheorghiu, Octavian Siedler, Philipp He, Ziming Erdincer, Baris UCL Bartlett Sch Architecture 22 Gordon St London WC1H 0QB England

To address the unprecedented challenges of construction pressurized by the global climate crisis, housing shortage, and growing shortage of skilled labor, this research presents a radical shift in the construction lifecycle of buildings, from linear processes that produce static continuous buildings to interrelational processes linking adaptative eco-systems of collaborative robots and reconfigurable building parts. Inspired by natural builders, the interdisciplinary field of collective robotic construction (CRC) offers the potential for scalable, adaptive, and resilient construction with simple robots. We establish a design framework for autonomous collaborative robotic construction (ACRC) through modular robotic material eco-systems (MRMES) trained with deep multi-agent reinforcement learning (DMARL). This involves the integration of three core aspects: (1) modular robotic material eco-systems (2) cyber-physical simulation and control with bidirectional feedback (3) adaptive intelligence through deep multi-agent reinforcement learning. The framework is implemented through three comparable case studies for collaborative modular robotic assembly of reconfigurable building parts.

关键词： distributed robotics artificial intelligence reinforcement learning multi-agent collective robotic construction CRC simulation computational design modular systems multi-agent reinforcement learning cyber-physical

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A Force-Mediated Controller for Cooperative Object Manipulation with Independent Autonomous Robots 1

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16th International Symposium on distributed Autonomous Robotic Systems (DARS)

作者： Carey, Nicole E. Werfel, Justin Autodesk Inc Autodesk Robot Lab San Francisco CA 94105 USA Harvard Univ Harvard John A Paulson Sch Engn & Appl Sci Boston MA 02115 USA

ISBN: (数字)9783031514975

ISBN: (纸本)9783031537035;9783031514975;9783031514968

We consider cooperative manipulation by multiple robots assisting a leader, when information about the manipulation task, environment, and team of helpers is unavailable, and without the use of explicit communication. The shared object being manipulated serves as a physical channel for coordination, with robots sensing forces associated with its movement. Robots minimize force conflicts, which are unavoidable under these restrictions, by inferring an intended context: decomposing the object's motion into a task space of allowed motion and a null space in which perturbations are rejected. The leader can signal a change in context by applying a sustained strong force in an intended new direction. We present a controller, prove its stability, and demonstrate its utility through experiments with (a) an in-lab force-sensitive robot assisting a human operator and (b) a multi-robot collective in simulation.

关键词： robot cooperation distributed robotics manipulation force-based control

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Roaming the Red Planet: Revolutionizing Mars Exploration with Dynamic Mobile Infrastructure

Roaming the Red Planet: Revolutionizing Mars Exploration wit...

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IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

作者： Santoro, Luca Brunelli, Davide Fontanelli, Daniele Univ Trento Dept Ind Engn Trento Italy

ISBN: (纸本)9798350380903;9798350380910

Navigation in unknown environments has emerged as an increasingly pivotal area of research, with autonomous robots assuming repetitive or hazardous tasks that would be challenging for humans. The complexities intrinsic to space exploration highlight the imperative for autonomous systems to support astronauts in their missions. A key challenge in this domain revolves around the realisation of a positioning service analogous to Earth's Global Navigation Satellite System. Traditionally, a common approach involves deploying a static infrastructure of beacons or anchors strategically placed within the exploration area to support agent position computation. This paper presents an innovative solution, employing a swarm of mobile unmanned aerial vehicles that dynamically follow and assist ground entities and uses ranging only measurements. This approach effectively addresses the cooperative localisation problem, eliminating the reliance on GNSS systems and pre-deployed beacon infrastructure. Notably, this novel approach not only removes these dependencies but also extends its positioning service capabilities to an unlimited number of entities, representing a significant advancement in navigation solutions tailored for space exploration. Simulation results validate the effectiveness of the proposed positioning framework. Even in the most challenging scenarios, the mean error in the computed position by the ground entity remains within a maximum margin of 50 centimetres with common ranging uncertainties.

关键词： Range-based localisation distributed robotics Robotic exploration

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Decentralized Risk-Aware Tracking of Multiple Targets 16th

Decentralized Risk-Aware Tracking of Multiple Targets

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16th International Symposium on distributed Autonomous Robotic Systems (DARS)

作者： Liu, Jiazhen Zhou, Lifeng Ramachandran, Ragesh Sukhatme, Gaurav S. Kumar, Vijay Univ Penn Philadelphia PA 19104 USA Univ Southern Calif Los Angeles CA 90007 USA

ISBN: (纸本)9783031537035;9783031514975;9783031514968

We consider the setting where a team of robots is tasked with tracking multiple targets with the following property: approaching the targets enables more accurate target position estimation, but also increases the risk of sensor failures. Therefore, it is essential to address the trade-off between tracking quality maximization and risk minimization. In the previous work [1], a centralized controller is developed to plan motions for all the robots - however, this is not a scalable approach. Here, we present a decentralized and risk-aware multi-target tracking framework, in which each robot plans its motion trading off tracking accuracy maximization and aversion to risk, while only relying on its own information and information exchanged with its neighbors. We use the control barrier function to guarantee network connectivity throughout the tracking process. Extensive numerical experiments demonstrate that our system can achieve similar tracking accuracy and risk-awareness to its centralized counterpart.

关键词： distributed robotics multi-target tracking risk-awareness connectivity maintenance

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Bout-based Gas Source Localization using Aerial Robot Swarms

Bout-based Gas Source Localization using Aerial Robot Swarms

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IEEE Sensors Conference

作者： Haeusler, Felix Stuehrenberg, Jan Smarsly, Kay Neumann, Patrick P. Hamburg Univ Technol Hamburg Germany BAM Fed Inst Mat Res & Testing Berlin Germany

ISBN: (纸本)9798350303872

Gas source localization (GSL) helps mitigate the impact of industrial accidents and natural disasters. While GSL may be dangerous and time-consuming when performed by humans, swarms of agile and inexpensive nano aerial robots may increase the safety and efficiency of gas source localizations. Since the small payloads of nano aerial robots limit the sensing and computing resources, strategies adapted from biological swarms, such as colonies of social insects, are used to coordinate robot swarms. Most swarm GSL strategies are based on the assumption that the maxima of gas concentrations are sufficiently close to the gas sources. However, prior studies have indicated that the occurrence of "bouts", a metric for the intermittency of gas distributions, may advantageously be used as a more accurate gas source proximity indicator. This paper presents a swarm GSL strategy employing bouts as source proximity indicators and a bio-inspired pheromone system for communication. Nano aerial robots, deployed in this study, act as agents and emit pheromone markers in an artificial environment upon detecting bouts. Leveraging the concept of artificial potential fields, the agents switch between exploiting the knowledge of the swarm by following pheromone gradients and exploring the search space by targeting a random point. The agents are repelled by each other and by walls to avoid collisions. The swarm GSL strategy is implemented into three nano aerial robots and validated in a real-world experiment in an indoor environment with a single gas source. The results indicate that the the swarm GSL strategy presented in this paper is capable of GSL in indoor environments and that the intermittency of gas distributions is a better source proximity indicator than the mean concentration.

关键词： Mobile robotic olfaction nano aerial robot gas source localization bouts distributed robotics

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Information transport in communication limited swarms

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ARTIFICIAL LIFE AND robotics 2022年第4期27卷 632-639页

作者： Wilson, James Hauert, Sabine Bristol Robot Lab Bristol Avon England Univ Bristol Dept Engn Math Bristol Avon England

Users and operators of swarms will, in the future, need to monitor the operations of swarms in a distributed way, without explicitly tracking every agent, and without the need for significant infrastructure or set up. Here we present a method for swarm self-monitoring that enables the aggregate display of information about swarm location by making use of physical transport of information and local communication. This method uses movement already exhibited by many swarms to collect self-reflective information in a fully distributed manner. We find that added swarm mobility can compensate for limited communication and that our self-monitoring swarm system scales well, with performance increasing with the size of the swarm in some cases. When developing systems such as this for real-world applications, individual agent memory will need to be taken into consideration, finding an effective means to spread swarm knowledge among robots while keeping information accessible to users.

关键词： Swarm robotics Swarm monitoring Information extraction distributed robotics

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