5,794 research outputs found

    The need for combining implicit and explicit communication in cooperative robotic systems

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    As the number of robots used in warehouses and manufacturing increases, so too does the need for robots to be able to manipulate objects, not only independently, but also in collaboration with humans and other robots. Our ability to effectively coordinate our actions with fellow humans encompasses several behaviours that are collectively referred to as joint action, and has inspired advances in human-robot interaction by leveraging our natural ability to interpret implicit cues. However, our capacity to efficiently coordinate on object manipulation tasks remains an advantageous process that is yet to be fully exploited in robotic applications. Humans achieve this form of coordination by combining implicit communication (where information is inferred) and explicit communication (direct communication through an established channel) in varying degrees according to the task at hand. Although these two forms of communication have previously been implemented in robotic systems, no system exists that integrates the two in a task-dependent adaptive manner. In this paper, we review existing work on joint action in human-robot interaction, and analyse the state-of-the-art in robot-robot interaction that could act as a foundation for future cooperative object manipulation approaches. We identify key mechanisms that must be developed in order for robots to collaborate more effectively, with other robots and humans, on object manipulation tasks in shared autonomy spaces

    A Survey and Analysis of Multi-Robot Coordination

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    International audienceIn the field of mobile robotics, the study of multi-robot systems (MRSs) has grown significantly in size and importance in recent years. Having made great progress in the development of the basic problems concerning single-robot control, many researchers shifted their focus to the study of multi-robot coordination. This paper presents a systematic survey and analysis of the existing literature on coordination, especially in multiple mobile robot systems (MMRSs). A series of related problems have been reviewed, which include a communication mechanism, a planning strategy and a decision-making structure. A brief conclusion and further research perspectives are given at the end of the paper

    A Nonlinear Model Predictive Control Scheme for Cooperative Manipulation with Singularity and Collision Avoidance

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    This paper addresses the problem of cooperative transportation of an object rigidly grasped by NN robotic agents. In particular, we propose a Nonlinear Model Predictive Control (NMPC) scheme that guarantees the navigation of the object to a desired pose in a bounded workspace with obstacles, while complying with certain input saturations of the agents. Moreover, the proposed methodology ensures that the agents do not collide with each other or with the workspace obstacles as well as that they do not pass through singular configurations. The feasibility and convergence analysis of the NMPC are explicitly provided. Finally, simulation results illustrate the validity and efficiency of the proposed method.Comment: Simulation results with 3 agents adde

    A Multi-Robot System Based on A Hybrid Communication Approach

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    Communication plays an important role in a multi-robot system. In a large system with many robots, it is difficult for all robots to exchange information at a time because of their limited communication capacities. On the other hand, sometimes there is such a situation where no explicit communication is allowed between robots. Therefore, efficient and reliable communication together with non-explicit communication is crucial for a multi-robot system. This paper presents a hybrid communication approach for a multi-robot system, which combines the explicit with implicit communications via using the prediction of robotic behaviour and a fuzzy communication approach. The hybrid communication approach contains a robot performance rule base, a fuzzy inference engine, and a semantics and grammar for communicating. Based on the hybrid communication strategy, the avoidance of collision with multiple robots in working area and multiple robots transporting a common object have been explored. The results of simulation show that the multi-robot system can complete a cooperative task successfully

    A cooperative architecture based on social insects

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    In the last two decades, cooperative robotic groups have advanced rapidly; beginning with simple, almost blind box pushing tasks and advancing to the complexity of robocup's autonomous soccer matches. Groups of machines have been employed to build structures, search for targets, mimic insects and enact complex formations with precision and aplomb. The complexity of the tasks accomplished have been both impressive and practical,clearly illustrating the potential power of robotic groups and demonstrating how they may be applied to solve real-world problems. Building on this success, we have created a software architecture that was intended to remove the robotic agents' dependency on complex communications or detailed task specific information. By incorporating biological models of stigmergic social insect cooperation into the architecture, we aim to ensure that the robots will be able to cooperate implicitly, without regard to group size and with only a weak dependency on task specific information and group homogeneity. We have conducted preliminary investigations into the design's feasibility by using computer simulations of a simple object passing task. This simple task has enabled us to establish that cooperation is possible using this system. This paper will discuss the system's origins, design and future expansion

    Robust Cooperative Manipulation without Force/Torque Measurements: Control Design and Experiments

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    This paper presents two novel control methodologies for the cooperative manipulation of an object by N robotic agents. Firstly, we design an adaptive control protocol which employs quaternion feedback for the object orientation to avoid potential representation singularities. Secondly, we propose a control protocol that guarantees predefined transient and steady-state performance for the object trajectory. Both methodologies are decentralized, since the agents calculate their own signals without communicating with each other, as well as robust to external disturbances and model uncertainties. Moreover, we consider that the grasping points are rigid, and avoid the need for force/torque measurements. Load distribution is also included via a grasp matrix pseudo-inverse to account for potential differences in the agents' power capabilities. Finally, simulation and experimental results with two robotic arms verify the theoretical findings

    A general architecture for robotic swarms

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    Swarms are large groups of simplistic individuals that collectively solve disproportionately complex tasks. Individual swarm agents are limited in perception, mechanically simple, have no global knowledge and are cheap, disposable and fallible. They rely exclusively on local observations and local communications. A swarm has no centralised control. These features are typifed by eusocial insects such as ants and termites, who construct nests, forage and build complex societies comprised of primitive agents. This project created the basis of a general swarm architecture for the control of insect-like robots. The Swarm Architecture is inspired by threshold models of insect behaviour and attempts to capture the salient features of the hive in a closely defined computer program that is hardware agnostic, swarm size indifferent and intended to be applicable to a wide range of swarm tasks. This was achieved by exploiting the inherent limitations of swarm agents. Individual insects were modelled as a machine capable only of perception, locomotion and manipulation. This approximation reduced behaviour primitives to a fixed tractable number and abstracted sensor interpretation. Cooperation was achieved through stigmergy and decisions made via a behaviour threshold model. The Architecture represents an advance on previous robotic swarms in its generality - swarm control software has often been tied to one task and robot configuration. The Architecture's exclusive focus on swarms, sets it apart from existing general cooperative systems, which are not usually explicitly swarm orientated. The Architecture was implemented successfully on both simulated and real-world swarms
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