The Khepera IV Mobile Robot: Performance Evaluation, Sensory Data and Software Toolbox

Soares, Jorge M.; Navarro, Iñaki; Martinoli, Alcherio

doi:10.1007/978-3-319-27146-0_59

Cited by 43 publications

(23 citation statements)

References 13 publications

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“…The robots in the swarm communicate using either IR or radio. The Khepera IV (Soares et al, 2016 ) is designed for any indoor lab application. A Linux core, color camera, WLAN, Bluetooth, USB Host, accelerometer, gyroscope, microphone, loudspeaker, three top RGB LEDs, and improved odometry makes it a compact and complete research platform for swarms in different scenarios.…”

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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Section: Swarm Applicationsmentioning

confidence: 99%

Swarm Robotic Behaviors and Current Applications

et al. 2020

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“…All algorithms were tested on Khepera IV robots [22] [23] in a wind tunnel of 20 × 4 × 2 m 3 , setting the maximum speed to 1 m/s and focusing on the upper part of the channel, see Fig. 3-5.…”

Section: A Environmentmentioning

confidence: 99%

Adaptive Lévy Taxis for odor source localization in realistic environmental conditions

Emery

Rahbar

Marjovi

et al. 2017

2017 IEEE International Conference on Robotics and Automation (ICRA)

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Odor source localization with mobile robots has recently been subject to many research works, but remains a challenging task mainly due to the large number of environmental parameters that make it hard to describe gas concentration fields. We designed a new algorithm called Adaptive Lévy Taxis (ALT) to achieve odor plume tracking through a correlated random walk. In order to compare its performances with well-established solutions, we have implemented three mothinspired algorithms on the same robotic platform. To improve the performance of the latter algorithms, we developed a rigorous way to determine one of their key parameters, the odor concentration threshold at which the robot considers to be inside or outside the plume. The methods have been systematically evaluated in a large wind tunnel under various environmental conditions. Experiments revealed that the performance of ALT is consistently good in all environmental conditions (in particular when compared to the three reference algorithms) in terms of both distance traveled to find the source and success rate.

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“…5 (right), the Khepera IV robots [40] are augmented with an odor sensing board and an anemometer board (explained in detail in [41]). Instead of using infrared ranging, for which we only have 2-D capable hardware, the absolute positions received from SwisTrack and the traversing system are merged in an external interface application, and the resulting range, bearing, and elevation data are sent to the robots over the network.…”

Section: B Wind Tunnel Experimentsmentioning

confidence: 99%

Towards 3-D distributed odor source localization: An extended graph-based formation control algorithm for plume tracking

Soares¹,

Marjovi²,

Giezendanner³

et al. 2016

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-The large number of potential applications for robotic odor source localization has motivated the development of a variety of plume tracking algorithms, the majority of which work in restricted two-dimensional scenarios. In this paper, we introduce a distributed algorithm for 3-D plume tracking using a system of ground and aerial robots in formation. We propose an algorithm that takes advantage of spatially distributed measurements to track the plume in 3-D and lead the robots to the source by integrating three behaviors -upwind movement, plume centering, and Laplacian feedback formation control. We evaluate this strategy in simulation and with real robots in a wind tunnel. For a source close to the ground, results show that a team of robots running our algorithm reaches the source with low lateral error while also tracing the horizontal and vertical plume shape.

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The Khepera IV Mobile Robot: Performance Evaluation, Sensory Data and Software Toolbox

Cited by 43 publications

References 13 publications

Swarm Robotic Behaviors and Current Applications

Swarm Robotic Behaviors and Current Applications

Adaptive Lévy Taxis for odor source localization in realistic environmental conditions

Towards 3-D distributed odor source localization: An extended graph-based formation control algorithm for plume tracking

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