A Two Teraflop Swarm

Jones, Simon; Studley, Matthew; Hauert, Sabine; Winfield, Alan

doi:10.3389/frobt.2018.00011

Cited by 12 publications

(11 citation statements)

References 67 publications

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“…Constrained computational resources represent such a hurdle. This argument is supported by recent work, such as [45], where computational extensions 7 are built for an existing miniature robot to specifically overcome the reality gap in evolutionary robotics.…”

Section: Discussionmentioning

confidence: 89%

Computational Resources of Miniature Robots: Classification and Implications

Trenkwalder

2019

IEEE Robot. Autom. Lett.

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When it comes to describing robots, many roboticists choose to focus on the size, types of actuators or other physical capabilities. As most areas of robotics deploy robots with large memory and processing power, the question "how computational resources limit what a robot can do" is often overlooked. However, the capabilities of many miniature robots are limited by significantly less memory and processing power. At present, there is no systematic approach to comparing and quantifying the computational resources as a whole and their implications.This paper proposes computational indices that systematically quantify computational resources-individually and as a whole. Then, by comparing 31 state-of-the-art miniature robots, a computational classification ranging from non-computing to minimally-constrained robots is introduced. Finally, the implications of computational constraints on robotic software are discussed.

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Section: Discussionmentioning

confidence: 89%

Computational Resources of Miniature Robots: Classification and Implications

Trenkwalder

2019

IEEE Robot. Autom. Lett.

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“…The Xpuck is an extension of the e-puck in terms of aggregate raw processing power (as used in modern mobile system-on-chip devices) of two teraflops. Thus, higher-individual robot computation can be achieved, e.g., image processing using the ArUco Marker tracking (Jones et al, 2018 ). The Thymio II robot (Riedo et al, 2013 ) targets the understanding of programming and robotic concepts using a wide range of sensors, including temperature, infrared distance, accelerometer, and microphone.…”

Section: Swarm Applicationsmentioning

confidence: 99%

Swarm Robotic Behaviors and Current Applications

et al. 2020

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In swarm robotics multiple robots collectively solve problems by forming advantageous structures and behaviors similar to the ones observed in natural systems, such as swarms of bees, birds, or fish. However, the step to industrial applications has not yet been made successfully. Literature is light on real-world swarm applications that apply actual swarm algorithms. Typically, only parts of swarm algorithms are used which we refer to as basic swarm behaviors. In this paper we collect and categorize these behaviors into spatial organization, navigation, decision making, and miscellaneous. This taxonomy is then applied to categorize a number of existing swarm robotic applications from research and industrial domains. Along with the classification, we give a comprehensive overview of research platforms that can be used for testing and evaluating swarm behavior, systems that are already on the market, and projects that target a specific market. Results from this survey show that swarm robotic applications are still rare today. Many industrial projects still rely on centralized control, and even though a solution with multiple robots is employed, the principal idea of swarm robotics of distributed decision making is neglected. We identified mainly following reasons: First of all, swarm behavior emerging from local interactions is hard to predict and a proof of its eligibility for applications in an industrial context is difficult to provide. Second, current communication architectures often do not match requirements for swarm communication, which often leads to a system with a centralized communication infrastructure. Finally, testing swarms for real industrial applications is an issue, since deployment in a productive environment is typically too risky and simulations of a target system may not be sufficiently accurate. In contrast, the research platforms present a means for transforming swarm robotics solutions from theory to prototype industrial systems.

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“…Robotic System Papers Manipulators [100], [4], [139], [59], [123], [124], [125], [24], [30], [35], [22], [9] Mobile Manipulators [23], [26], [27], [22], [138], [50], [73], [82], [147], [54], [182] Wheeled Robots [153], [154], [6], [1], [2], [96] Robot Swarms [87], [76], [77], [106], [107], [171] Humanoid Robots [30], [9], [101], [164], [64], [33] Autonomous vehicles [28], [115] Aerial Robots [83], [84], [85], [86], [145], [89], [19],...…”

Section: Tablementioning

confidence: 99%

“…In swarm robotics, a number of studies have been made on the combination of BTs and evolutional algorithms [76,77,87,106,107,122,171]. The tree structure of BTs gives good support for straight-forward implementation of both mutations and cross over, while the modularity increases the chances of such variations resulting in functional designs.…”

Section: Mobile Ground Robotsmentioning

confidence: 99%