A Framework for Multi-Robot Coordination (original) (raw)

Robust Multi-Robot Coordination in Noisy and Dangerous Environments

2005

In this paper we present the design and implementation of a complete framework for multi-robot coordination in which robots collectively execute interdependent tasks of an overall complex mission requiring diverse capabilities. Given a heterogeneous team of robots and task dependencies, proposed framework provides a distributed, robust mechanism for assigning robots to tasks in an order that efficiently completes the mission. The approach is robust to unreliable communication and robot failures. It is market-based approach, and therefore scalable, but it does not provide guarantees of optimality. In order to obtain optimum allocations in noisy environments we introduce a coalition maintenance scheme for dynamic reconfiguration of the assigned tasks at run time. Additional routines, called precautions are added in the framework for addressing different types of failures common in robot systems and solving conflicts in cases of these failures. Framework has been tested in simulations that include variable message loss rates and robot failures. We expect to port the system to mobile robots in the future. Our experiments illustrate effectiveness of the proposed approach in realistic scenarios.

CoMutaR: A framework for multi-robot coordination and task allocation

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009

In multi-robot systems, task allocation and coordination are two fundamental problems that share high synergy. Although multi-robot architectures typically separate them into distinct layers, relevant improvement may be expected from solutions that are able to concurrently handle them at the same "level". This paper proposes a novel framework, called CoMutaR (Coalition formation based on Multitasking Robots), which is used for both tackle task distribution among teams of mobile robots, and to guarantee the coordination within the formed teams. Robot capabilities are modelled as actions, independent modules whose inputs do not depend on the robot that generated it. Solutions to tasks are devised as coalitions of actions, that can be spread amongst the available robots. We also define the concept of share-restricted resources, which are periodically checked and updated by the actions in the system. In contrast to prior approaches, this mechanism enables to quickly determine if two actions can be executed simultaneously, allowing a single robot to execute multiple tasks concurrently. A single-round auction protocol is used to automatically discover and form coalitions. Once a coalition is formed, coordination among robots is modelled as constraints imposed over the share-restricted resources. Finally, we have successfully implemented and applied CoMutaR in typical scenarios like object transportation, area surveillance, and multi-robot box pushing. Experimental results demonstrate that the system is able to provide good solutions even in the case of severe failures in participating robots.

Planning to fail: using reliability to improve multirobot task allocation

Unattended Ground, Sea, and Air Sensor Technologies and Applications XII, 2010

The reliability of individual robots influences the success of multirobot missions. When one robot fails, others must be retasked to complete the failed robot's tasks. This increases the failure likelihood for these other robots. Existing multirobot task allocation systems consider robot failures only after the fact, via replanning. In this paper we show that mission performance for multirobot missions can be improved by using knowledge of robot failure rates to inform the initial task allocation.

Multi-robot team coordination through roles, positionings and coordinated procedures

2009

The coordination methodologies of CAMBADA, a robotic soccer team designed to participate in the RoboCup middle-size league (MSL), are presented. The approach, which relies on information sharing and integration within the team, is based on formations, flexible positionings and dynamic role and positioning assignment. Role/positioning assignment follows a new priority-based algorithm that maintains a competitive formation, covering the most important roles/positionings when malfunctions lead to a reduction of the team size. Coordinated procedures for passing and setplays have also been implemented. With this design, CAMBADA reached the 1st place in the RoboCup'2008 world championship. Competition results and performance measures computed from logs and videos of real competition games are presented and discussed. I. INTRODUCTION S robots become increasingly available in different areas of human activity, researchers are naturally prompted to investigate how robots can cooperate with each in order to perform different tasks. Moreover, progress in wireless communication technologies enables information sharing and explicit coordination between robots. These are basic capabilities needed to support sophisticated cooperation and coordination algorithms. Given this increasing availability of robots and communication technologies, multi-robot systems have, in the last two decades, been receiving more and more attention from researchers [2][43][8]. Interest on multi-robot systems is further justified by the advantages they offer with respect to single robots. First, some tasks are simply too difficult or impossible to be carried out by a single robot. In other cases, by providing a larger work force, multi-robot systems can carry out tasks faster. Multi-robot systems also facilitate scalability, as larger problems can often be solved by adding more robots to the team. Finally, through their inherent redundancy, multi-robot systems offer robustness, as they may still work when a team member is damaged or malfunctioning. These advantages make multi-robot systems useful in a variety of domains, such as exploration of unknown or Nuno Lau and Luís Seabra Lopes are with the ATRI/IEETA as well as with the

Auction-based Fault-Tolerant Multi-Robot Cooperation

Engineering and Applied Science, 2012

This paper presents a market driven approach for robust multi-robot cooperation. The example task that is considered is object transportation from an original location to a goal location. The developed methodology relies on market-based decision making, which uses auction as a process of assigning a task to a robot by offering it up for a bid. In the event of robot failure during the execution of a task, the task is re-allocated to another suitable robot using the same auctioning process. This paper addresses two possible robot malfunctions-partial and full failures, which can happen any time during the execution of a task. The practicability of the developed methodology is demonstrated by implementing an auction-based approach on a team of simulated robots that cooperatively execute a task.

Complex Tasks Allocation for Multi Robot Teams under Communication Constraints

The Multirobot Task Allocation (MRTA) paradigm is widely used in multirobot cooperation schemes, e.g. for observation, surveillance and tracking missions. Market-based approaches have yielded effective distributed solutions for such missions, showing the ability to manage heterogeneous, dynamic and robust robot teams. Two major challenges remain however poorly tackled: the management of inter-robot and inter-task communication constraints, and the use of a rich task formalism to model complex missions. This paper presents our investigations to treat these two aspects. The inter-robot and inter-task communication constraints are explicitly handled in the task allocation process, through simple geometric models and thanks to temporal scheduling skills. Rich tasks are allocated using a treebased task formalism that allows to treat complex missions with task ordering. Current work has shown it to be able to handle more complex tasks and to give better solution than MRTA systems working on simple task structures. In our work we will try to go further in this investigation.

A Generic Framework for Distributed Multirobot Cooperation

Journal of Intelligent and Robotic Systems

DEMiR-CF is a generic framework designed for a multirobot team to efficiently allocate tasks among themselves and achieve an overall mission. In the design of DEMiR-CF, the following issues were particularly investigated as the design criteria: efficient and realistic representation of missions, efficient allocation of tasks to cooperatively achieve a global goal, maintenance of the system coherence and consistency by the team members, detection of the contingencies and recover from various failures that may arise during runtime, efficient reallocation of tasks (if necessary) and reorganization of team members (if necessary). DEMiR-CF is designed to address different types of missions from the simplest to more complex ones, including missions with interrelated tasks and multi-resource (robot) requirements. Efficiency of the framework is validated through experiments in three different types of domains.

Simultaneous Auctions for" Rendez-Vous" Coordination Phases in Multi-robot Multi-task Mission

This paper presents a protocol that permits to automatically allocate tasks, in a distributed way, among a fleet of agents when communication is not permanently available. In cooperation settings when communication is available only during short periods, it is difficult to build joint policies of agents to collectively accomplish a mission defined by a set of tasks. The proposed approach aims to punctually coordinate the agents during "Rendez-vous" phases defined by the short periods when communication is available. This approach consists of a series of simultaneous auctions to coordinate individual policies computed in a distributed way from Markov decision processes oriented by several goals. These policies allow the agents to evaluate their own relevance in each task achievement and to communicate bids when possible. This approach is illustrated on multi-mobile-robot missions similar to distributed traveling salesmen problem. Experimental results (through simulation and on real robots) demonstrate that high-quality allocations are quickly computed.

Simultaneous Auctions for "Rendez-Vous" Coordination Phases in Multi-robot Multi-task Mission

2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2013

Planning to fail — Reliability needs to be considered a priori in multirobot task allocation

2009 IEEE International Conference on Systems, Man and Cybernetics, 2009

The reliability of individual team members has a substantial and complex influence on the success of multirobot missions. When one robot fails, other robots must be retasked to complete the tasks that were assigned to the failed robot. This in turn increases the likelihood of these other robots failing, since they have more work to do. Existing multirobot task allocation systems consider robot failures only after the fact-by replanning after a failure occurs. We hypothesize that it should be important to consider robot reliabilities when generating an initial plan. In this paper we test this hypothesis in the context of the multirobot exploration problem. We take a simple exhaustive planner and compare the plan it chooses against the optimal plan that takes into account robot failures and the backup plans that occur after failure. Our results show that for this problem domain, making an initial plan without regards to individual robot reliabilities results in choosing a suboptimal plan most of the time, and that the difference in mission performance between the chosen plan and the optimal plan is usually substantial. In brief, in order to successfully plan we must 'plan to fail'.

A Framework for Multi-Robot Coordination (original) (raw)

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