129 research outputs found

    A Bio-Inspired Model for Visual Collision Avoidance on a Hexapod Walking Robot

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    Meyer HG, Bertrand O, Paskarbeit J, Lindemann JP, Schneider A, Egelhaaf M. A Bio-Inspired Model for Visual Collision Avoidance on a Hexapod Walking Robot. In: Lepora FN, Mura A, Mangan M, Verschure FMJP, Desmulliez M, Prescott JT, eds. Biomimetic and Biohybrid Systems: 5th International Conference, Living Machines 2016, Edinburgh, UK, July 19-22, 2016. Proceedings. Cham: Springer International Publishing; 2016: 167-178.While navigating their environments it is essential for autonomous mobile robots to actively avoid collisions with obstacles. Flying insects perform this behavioural task with ease relying mainly on information the visual system provides. Here we implement a bioinspired collision avoidance algorithm based on the extraction of nearness information from visual motion on the hexapod walking robot platform HECTOR. The algorithm allows HECTOR to navigate cluttered environments while actively avoiding obstacles

    NeuroPod: a real-time neuromorphic spiking CPG applied to robotics

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    Initially, robots were developed with the aim of making our life easier, carrying out repetitive or dangerous tasks for humans. Although they were able to perform these tasks, the latest generation of robots are being designed to take a step further, by performing more complex tasks that have been carried out by smart animals or humans up to date. To this end, inspiration needs to be taken from biological examples. For instance, insects are able to optimally solve complex environment navigation problems, and many researchers have started to mimic how these insects behave. Recent interest in neuromorphic engineering has motivated us to present a real-time, neuromorphic, spike-based Central Pattern Generator of application in neurorobotics, using an arthropod-like robot. A Spiking Neural Network was designed and implemented on SpiNNaker. The network models a complex, online-change capable Central Pattern Generator which generates three gaits for a hexapod robot locomotion. Recon gurable hardware was used to manage both the motors of the robot and the real-time communication interface with the Spiking Neural Networks. Real-time measurements con rm the simulation results, and locomotion tests show that NeuroPod can perform the gaits without any balance loss or added delay.Ministerio de Economía y Competitividad TEC2016-77785-

    Improved Collision Perception Neuronal System Model with Adaptive Inhibition Mechanism and Evolutionary Learning

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    Accurate and timely perception of collision in highly variable environments is still a challenging problem for artificial visual systems. As a source of inspiration, the lobula giant movement detectors (LGMDs) in locust’s visual pathways have been studied intensively, and modelled as quick collision detectors against challenges from various scenarios including vehicles and robots. However, the state-of-the-art LGMD models have not achieved acceptable robustness to deal with more challenging scenarios like the various vehicle driving scenes, due to the lack of adaptive signal processing mechanisms. To address this problem, we propose an improved neuronal system model, called LGMD+, that is featured by novel modelling of spatiotemporal inhibition dynamics with biological plausibilities including 1) lateral inhibitionswithglobalbiasesdefinedbyavariantofGaussiandistribution,spatially,and2)anadaptivefeedforward inhibition mediation pathway, temporally. Accordingly, the LGMD+ performs more effectively to detect merely approaching objects threatening head-on collision risks by appropriately suppressing motion distractors caused by vibrations, near-miss or approaching stimuli with deviations from the centre view. Through evolutionary learning with a systematic dataset of various crash and non-collision driving scenarios, the LGMD+ shows improved robustness outperforming the previous related methods. After evolution, its computational simplicity, flexibility and robustness have also been well demonstrated by real-time experiments of autonomous micro-mobile robots

    Trends in the control of hexapod robots: a survey

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    The static stability of hexapods motivates their design for tasks in which stable locomotion is required, such as navigation across complex environments. This task is of high interest due to the possibility of replacing human beings in exploration, surveillance and rescue missions. For this application, the control system must adapt the actuation of the limbs according to their surroundings to ensure that the hexapod does not tumble during locomotion. The most traditional approach considers their limbs as robotic manipulators and relies on mechanical models to actuate them. However, the increasing interest in model-free models for the control of these systems has led to the design of novel solutions. Through a systematic literature review, this paper intends to overview the trends in this field of research and determine in which stage the design of autonomous and adaptable controllers for hexapods is.The first author received funding through a doctoral scholarship from the Portuguese Foundation for Science and Technology (FCT) (Grant No. SFRH/BD/145818/2019), with funds from the Portuguese Ministry of Science, Technology and Higher Education and the European Social Fund through the Programa Operacional Regional Norte. This work has been supported by the FCT national funds, under the national support to R&D units grant, through the reference project UIDB/04436/2020 and UIDP/04436/2020

    Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

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    Walking animals, like insects, with little neural computing can effectively perform complex behaviors. They can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a walking robot is a challenging task. In this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a biomechanical walking robot. The turning information is transmitted as descending steering signals to the locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations as well as escaping from sharp corners or deadlocks. Using backbone joint control embedded in the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments

    Telelocomotion—remotely operated legged robots

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    © 2020 by the authors. Li-censee MDPI, Basel, Switzerland. Teleoperated systems enable human control of robotic proxies and are particularly amenable to inaccessible environments unsuitable for autonomy. Examples include emergency response, underwater manipulation, and robot assisted minimally invasive surgery. However, teleoperation architectures have been predominantly employed in manipulation tasks, and are thus only useful when the robot is within reach of the task. This work introduces the idea of extending teleoperation to enable online human remote control of legged robots, or telelocomotion, to traverse challenging terrain. Traversing unpredictable terrain remains a challenge for autonomous legged locomotion, as demonstrated by robots commonly falling in high-profile robotics contests. Telelocomotion can reduce the risk of mission failure by leveraging the high-level understanding of human operators to command in real-time the gaits of legged robots. In this work, a haptic telelocomotion interface was developed. Two within-user studies validate the proof-of-concept interface: (i) The first compared basic interfaces with the haptic interface for control of a simulated hexapedal robot in various levels of traversal complexity; (ii) the second presents a physical implementation and investigated the efficacy of the proposed haptic virtual fixtures. Results are promising to the use of haptic feedback for telelocomotion for complex traversal tasks

    Locomotion Control of Hexapod Walking Robot with Four Degrees of Freedom per Leg

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    V této práci představujeme nového šestinohého robota jménem HAntR, kterého jsme vytvořili dle potřeb Laboratoře výpočetní robotiky Centra umělé inteligence fakulty Elektrotechnické Českého vysokého učení technického v Praze. Jeho hlavním účelem jest vylepšit schopnosti pohybu v těžkém terénu původního robotu přidáním čtvrtého stupně volnosti každé noze. Na základě nově navržené nohy jsme také přepracovali celé tělo robotu tak, aby splnilo i další požadavky, jako například menší rozměry, či možnost osazení alespoň šesti Lithium-Iontovými monočlánky. V práci pečlivě popisujeme motivace a úvahy, které nás k výslednému návrhu vedly. Uvádíme řešení přímé i inverzní kinematické úlohy řešené pomocí podmínky na ideální orientaci konce nohy a uvažující i důležité kinematické singularity. Navržený robot byl vyzkoušen v několika experimentech, při kterých byl použit námi navržený řídicí systém napsaný v jazyce C++. Ukázalo se, že HAntR vydrží díky zvýšené energetické hustotě a lepšímu rozkladu sil v končetinách autonomně fungovat přes hodinu. Robot je také schopen jít rychlostí až 0.42m/s, což předčí mnohé srovnatelné roboty. Při experimentu, kdy robot stál na nakloněné rovině, bylo prokázáno zlepšení oproti předchozímu robotu. A také jsme dle pokynů této práce potvrdili, že i HAntR je schopen adaptivní chůze spoléhající pouze na poziční zpětnou vazbu.In this thesis a novel six-legged robot called HAntR is presented. The robot was developed according to needs of the Robotics Laboratory, at the Artificial Intelligent Center, Faculty of Electrical Engineering, Czech Technical University in Prague. Its main purpose is enhancing rough-terrain movement capabilities by upgrading a former design by adding fourth degree of freedom to each leg. We also revised robot torso to fit new leg design and incorporate other requirements such as smaller dimensions with space for at least six Lithium-Ion cells. We thoroughly describe motivations and considerations that led us to the presented particular solution. Further, the solutions of forward and inverse kinematic tasks with partial orientation constraint and important singularities avoidance are presented. The proposed design has been evaluated in several experimental deployments, which utilised developed software controller written in C++. Endurance tests showed, that HAntR is able to remotely operate for over an hour thanks to increased energy density. Maximal speed test resulted to 0.42m/s during tripod gait, which outpaces most of the comparable robotic platforms. Experiment where HAntR stood on platform with varying inclination showed qualitative improvement against former robot. Finally, in accord with the thesis assignment, we proved that HAntR is able to perform walking with adaptive gait using positional feedback only

    Climbing and Walking Robots

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    Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study
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