Autonomous Multi-robot Systems Research Articles

A PSO based multi-robot task allocation

Recent research trends and technology developments have been instrumental to the realisation of autonomous multi-robot systems (MRS) performing increasingly complex missions. However the selection of candidate robots from a team of robots for performing the task(s) from a set of desired tasks in order to achieve an economical and feasible process poses a difficult problem. Task distribution methodologies have to make sure that not only the global assignment is achieved, but also the tasks are well assigned among the robots. This paper presents the particle swarm optimisation (PSO) algorithm designed to address this problem. A two-phase solution methodology is used to solve the multi-robot task allocation (MRTA) problem wherein the task capability of the robots is determined during the first segment and the task allocation optimisation is done using PSO during the second segment. The solution to MRTA problem in dynamic environment is proposed using a novel PSO based algorithm and is compared with that using linear programming (LP).

Ad Hoc Wireless Networking and Shared Computation for Autonomous Multirobot Systems

A wireless ad hoc network is introduced that enables inter-robot communication and shared computation among multiple robots with PC/104-based single board computers running the real-time application interface patched Linux operating system. Through the use of IEEE 802.11 ad hoc technology and User Datagram Protocol, each robot is able to exchange data without the need of a centralized router or wireless access point. The paper presents three key aspects of this novel architecture to include: 1) procedures to install the real-time application interface patched operating system and wireless ad hoc communication protocol on a multiple robot system; 2) development of a Simulink ® library to enable intercommunication among robots and provide the requisite software-hardware interfaces for the onboard sensor suite and actuator packages; 3) methods to rapidly generate and deploy real-time executables using Mathwork’s Real-Time Workshop™ to enable an autonomous robotic system. Experimental test results from the Spacecraft Robotics Laboratory at the Naval Postgraduate School are presented which demonstrate negligible network latencies and real-time distributed computing capability on the Autonomous Spacecraft Assembly Test Bed. A complete manual is also included to replicate the network and software infrastructures described in this work. Also, the developed Simulink ® library can be requested from the authors.

Social Integration of Robots into Groups of Cockroaches to Control Self-Organized Choices

Collective behavior based on self-organization has been shown in group-living animals from insects to vertebrates. These findings have stimulated engineers to investigate approaches for the coordination of autonomous multirobot systems based on self-organization. In this experimental study, we show collective decision-making by mixed groups of cockroaches and socially integrated autonomous robots, leading to shared shelter selection. Individuals, natural or artificial, are perceived as equivalent, and the collective decision emerges from nonlinear feedbacks based on local interactions. Even when in the minority, robots can modulate the collective decision-making process and produce a global pattern not observed in their absence. These results demonstrate the possibility of using intelligent autonomous devices to study and control self-organized behavioral patterns in group-living animals.

Social Foraging Theory for Robust Multiagent System Design

An analogy between an agent (e.g., an autonomous vehicle) and a biological forager is extended to a social environment by viewing a communication network as implementing interagent sociality. We first describe engineering design within an evolutionary game-theoretic framework. We then explain why sociality may emerge in some environments and for some agent objectives. Next, we derive the evolutionarily stable design strategy for an agent manufacturer: 1) choosing whether the agent it produces should cooperate with other agents in a search problem and 2) choosing the group size of a multiagent system tasked with a cooperative search problem. We show the impact of "agent relatedness," a measure of common descent between two agents based on their underlying manufacturers, on the choices in scenarios 1) and 2). Our predictions are evaluated in an autonomous vehicle simulation testbed. The results illustrate a new methodology for manufacturers to make robust, optimal choices for multiagent system design for a given set of objectives and domain of operation. Note to Practitioners-The design of autonomous multirobot systems with various applications, such as in parts production or search and destroy operations in a military environment, is of growing importance. Here, we integrate economic and technical issues into an unified engineering design framework for the manufacturers of robots. Our approach leads to manufacturer design decisions that are robust relative to the market for a manufacturer's products. Robot component aspects, such as sensors and communications as well as mission performance aspects, can be captured and coupled into the design process. We use the design of intervehicle cooperation and robot group size to illustrate this approach. The practical significance lies in the fact that we take a broad perspective on engineering design, one closer to the real world, due to the considerations of marketplace economics. Moreover, the approach provides a framework to study design choices that escape systematic analysis in other frameworks (e.g., group size)

Multi-robot coalition formation

As the community strives towards autonomous multi-robot systems, there is a need for these systems to autonomously form coalitions to complete assigned missions. Numerous coalition formation algorithms have been proposed in the software agent literature. Algorithms exist that form agent coalitions in both super additive and non-super additive environments. The algorithmic techniques vary from negotiation-based protocols in multi-agent system (MAS) environments to those based on computation in distributed problem solving (DPS) environments. Coalition formation behaviors have also been discussed in relation to game theory. Despite the plethora of MAS coalition formation literature, to the best of our knowledge none of the proposed algorithms have been demonstrated with an actual multi-robot system. There exists a discrepancy between the multi-agent algorithms and their applicability to the multi-robot domain. This paper aims to bridge that discrepancy by unearthing the issues that arise while attempting to tailor these algorithms to the multi-robot domain. A well-known multi-agent coalition formation algorithm has been studied in order to identify the necessary modifications to facilitate its application to the multi-robot domain. This paper reports multi-robot coalition formation results based upon simulation and actual robot experiments. A multi-agent coalition formation algorithm has been demonstrated on an actual robot system.

Market-based Multirobot Coordination for Complex Tasks

Current technological developments and application-driven demands are bringing us closer to the realization of autonomous multi-robot systems performing increasingly complex missions. However, existing methods of distributing mission subcomponents among multirobot teams do not explicitly handle the required complexity and instead treat tasks as simple indivisible entities, ignoring any inherent structure and semantics that such complex tasks might have. These task properties can be exploited to produce more efficient team plans by giving individual robots the ability to come up with new, more localized ways to perform a task; by allowing multiple robots to cooperate by sharing the subcomponents of a task; or both. In this paper, we describe the complex task allocation problem and present a distributed solution for efficiently allocating a set of complex tasks among a robot team. Complex tasks are tasks that can be solved in many possible ways. In contrast, simple tasks can be accomplished in a straightforward, prescriptive manner. The current scope of our work is currently limited to complex tasks that can be decomposed into multiple subtasks related by Boolean logic operators. Our solution to multirobot coordination for complex tasks extends market-based approaches by generalizing task descriptions into task trees, which allows tasks to be traded in a market setting at variable levels of abstraction. In order to incorporate these task structures into a market mechanism, novel and efficient bidding and auction clearing algorithms are required. As an example scenario, we focus on an area reconnaissance problem which requires sensor coverage by a team of robots over a set of defined areas of interest. The advantages of explicitly modeling complex tasks during the allocation process is demonstrated by a comparison of our approach with existing task allocation algorithms in this application domain. In simulation we compare the quality of solution and the computation times of these different approaches. Implementations on two separate teams of indoor and outdoor robots further validates our approach.

A computer network based control architecture for autonomous distributed multirobot systems

This paper presents the specification and implementation procedure using a microcomputer network based autonomous distributed control architecture for industrial multirobot systems. The procedure is based on the concept of data flow network controlled by communicating sequential processes to perform coordinated tasks. Robots and other computerized industrial devices such as conveyors and manufacturing machines are defined as object-oriented Petri nets. A modular and hierarchical approach is adopted to define a set of Petri net type diagrams which represent concurrent activities of control processes for such devices. Asynchronous and synchronous interactions are modelled by places and transitions, respectively, in global process interaction nets. The control software is implemented on a computer network using Inmos transputers with true parallel processing and message passing primitives efficiently handled in hardware. Petri net based models are directly and efficiently transformed to corresponding codes in occam, the high level parallel programming language defined for the transputer.

Efficiency Assessment of Performance of Decentralized Autonomous Multi-Robot Systems

This paper presents a new methodology for the efficiency assessment of task performance of decentralized autonomous multi-robot system. This formulation considers the types of the robots (in terms of sensing, action, and control), the description of the environment (the world), the facts (rules) of the world, and the specifications of the tasks to be performed. The performance efficiency is defined in terms of the total time required for completing the task, total energy requirement, and the comparison of the final results and the desired results. A robot colony simulator was used to perform a number of experiments, measuring the task performance efficiency, of a colony of simulated robots which perform specific tasks in a virtual world. The experimental results are presented in this paper. This paper also describes a team of four robots designed and fabricated in hardware. The physical robots were used successfully to validate the results from the simulated colony.