136 research outputs found

    Bio-Inspired Robotics

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    Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensoryโ€“motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field

    Shape-based compliance control for snake robots

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    I serpenti robot sono una classe di meccanismi iper-ridondanti che appartiene alla robotica modulare. Grazie alla loro forma snella ed allungata e all'alto grado di ridondanza possono muoversi in ambienti complessi con elevata agilitร . L'abilitร  di spostarsi, manipolare e adattarsi efficientemente ad una grande varietร  di terreni li rende ideali per diverse applicazioni, come ad esempio attivitร  di ricerca e soccorso, ispezione o ricognizione. I robot serpenti si muovono nello spazio modificando la propria forma, senza necessitร  di ulteriori dispositivi quali ruote od arti. Tali deformazioni, che consistono in movimenti ondulatori ciclici che generano uno spostamento dell'intero meccanismo, vengono definiti andature. La maggior parte di esse sono ispirate al mondo naturale, come lo strisciamento, il movimento laterale o il movimento a concertina, mentre altre sono create per applicazioni specifiche, come il rotolamento o l'arrampicamento. Un serpente robot con molti gradi di libertร  deve essere capace di coordinare i propri giunti e reagire ad ostacoli in tempo reale per riuscire a muoversi efficacemente in ambienti complessi o non strutturati. Inoltre, aumentare la semplicitร  e ridurre il numero di controllori necessari alla locomozione alleggerise una struttura di controllo che potrebbe richiedere complessitร  per ulteriori attivitร  specifiche. L'obiettivo di questa tesi รจ ottenere un comportamento autonomo cedevole che si adatti alla conformazione dell'ambiente in cui il robot si sta spostando, accrescendo le capacitร  di locomozione del serpente robot. Sfruttando la cedevolezza intrinseca del serpente robot utilizzato in questo lavoro, il SEA Snake, e utilizzando un controllo che combina cedevolezza attiva ad una struttura di coordinazione che ammette una decentralizzazione variabile del robot, si dimostra come tre andature possano essere modificate per ottenere una locomozione efficiente in ambienti complessi non noti a priori o non modellabili

    In silico case studies of compliant robots: AMARSI deliverable 3.3

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    In the deliverable 3.2 we presented how the morphological computing ap- proach can significantly facilitate the control strategy in several scenarios, e.g. quadruped locomotion, bipedal locomotion and reaching. In particular, the Kitty experimental platform is an example of the use of morphological computation to allow quadruped locomotion. In this deliverable we continue with the simulation studies on the application of the different morphological computation strategies to control a robotic system

    Simulation and robotics studies of salamander locomotion: Applying neurobiological principles to the control of locomotion in robots

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    This article presents a project that aims at understanding the neural circuitry controlling salamander locomotion, and developing an amphibious salamander-like robot capable of replicating its bimodal locomotion, namely swimming and terrestrial walking. The controllers of the robot are central pattern generator models inspired by the salamander's locomotion control network. The goal of the project is twofold: (1) to use robots as tools for gaining a better understanding of locomotion control in vertebrates and (2) to develop new robot and control technologies for developing agile and adaptive outdoor robots. The article has four parts. We first describe the motivations behind the project. We then present neuromechanical simulation studies of locomotion control in salamanders. This is followed by a description of the current stage of the robotic developments. We conclude the article with a discussion on the usefulness of robots in neuroscience research with a special focus on locomotion contro

    Multiple chaotic central pattern generators with learning for legged locomotion and malfunction compensation

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    An originally chaotic system can be controlled into various periodic dynamics. When it is implemented into a legged robot's locomotion control as a central pattern generator (CPG), sophisticated gait patterns arise so that the robot can perform various walking behaviors. However, such a single chaotic CPG controller has difficulties dealing with leg malfunction. Specifically, in the scenarios presented here, its movement permanently deviates from the desired trajectory. To address this problem, we extend the single chaotic CPG to multiple CPGs with learning. The learning mechanism is based on a simulated annealing algorithm. In a normal situation, the CPGs synchronize and their dynamics are identical. With leg malfunction or disability, the CPGs lose synchronization leading to independent dynamics. In this case, the learning mechanism is applied to automatically adjust the remaining legs' oscillation frequencies so that the robot adapts its locomotion to deal with the malfunction. As a consequence, the trajectory produced by the multiple chaotic CPGs resembles the original trajectory far better than the one produced by only a single CPG. The performance of the system is evaluated first in a physical simulation of a quadruped as well as a hexapod robot and finally in a real six-legged walking machine called AMOSII. The experimental results presented here reveal that using multiple CPGs with learning is an effective approach for adaptive locomotion generation where, for instance, different body parts have to perform independent movements for malfunction compensation.Comment: 48 pages, 16 figures, Information Sciences 201

    ๋ถ„์‚ฐ๋œ ๋กœํ„ฐ๋กœ ๊ตฌ๋™๋˜๋Š” ๋น„ํ–‰ ์Šค์ผˆ๋ ˆํ†ค ์‹œ์Šคํ…œ์˜ ๋””์ž์ธ ์ƒํƒœ์ถ”์ • ๋ฐ ์ œ์–ด

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :๊ณต๊ณผ๋Œ€ํ•™ ๊ธฐ๊ณ„ํ•ญ๊ณต๊ณตํ•™๋ถ€,2020. 2. ์ด๋™์ค€.In this thesis, we present key theoretical components for realizing flying aerial skeleton system called LASDRA (large-size aerial skeleton with distributed rotor actuation). Aerial skeletons are articulated aerial robots actuated by distributed rotors including both ground connected type and flying type. These systems have recently attracted interest and are being actively researched in several research groups, with the expectation of applying those for aerial manipulation in distant/narrow places, or for the performance with entertaining purpose such as drone shows. Among the aerial skeleton systems, LASDRA system, proposed by our group has some significant advantages over the other skeleton systems that it is capable of free SE(3) motion by omni-directional wrench generation of each link, and also the system can be operated with wide range of configuration because of the 3DOF (degrees of freedom) inter-link rotation enabled by cable connection among the link modules. To realize this LASDRA system, following three components are crucial: 1) a link module that can produce omni-directional force and torque and enough feasible wrench space; 2) pose and posture estimation algorithm for an articulated system with high degrees of freedom; and 3) a motion generation framework that can provide seemingly natural motion while being able to generate desired motion (e.g., linear and angular velocity) for the entire body. The main contributions of this thesis is theoretically developing these three components, and verifying these through outdoor flight experiment with a real LASDRA system. First of all, a link module for the LASDRA system is designed with proposed constrained optimization problem, maximizing the guaranteed feasible force and torque for any direction while also incorporating some constraints (e.g., avoiding inter-rotor air-flow interference) to directly obtain feasible solution. Also, an issue of ESC-induced (electronic speed control) singularity is first introduced in the literature which is inevitably caused by bi-directional thrust generation with sensorless actuators, and handled with a novel control allocation called selective mapping. Then for the state estimation of the entire LASDRA system, constrained Kalman filter based estimation algorithm is proposed that can provide estimation result satisfying kinematic constraint of the system, also along with a semi-distributed version of the algorithm to endow with system scalability. Lastly, CPG-based motion generation framework is presented that can generate natural biomimetic motion, and by exploiting the inverse CPG model obtained with machine learning method, it becomes possible to generate certain desired motion while still making CPG generated natural motion.๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ๋น„ํ–‰ ์Šค์ผˆ๋ ˆํ†ค ์‹œ์Šคํ…œ LASDRA (large-size aerial skeleton with distributed rotor actuation) ์˜ ๊ตฌํ˜„์„ ์œ„ํ•ด ์š”๊ตฌ๋˜๋Š” ํ•ต์‹ฌ ๊ธฐ๋ฒ•๋“ค์„ ์ œ์•ˆํ•˜๋ฉฐ, ์ด๋ฅผ ์‹ค์ œ LASDRA ์‹œ์Šคํ…œ์˜ ์‹ค์™ธ ๋น„ํ–‰์„ ํ†ตํ•ด ๊ฒ€์ฆํ•œ๋‹ค. ์ œ์•ˆ๋œ ๊ธฐ๋ฒ•์€ 1) ์ „๋ฐฉํ–ฅ์œผ๋กœ ํž˜๊ณผ ํ† ํฌ๋ฅผ ๋‚ผ ์ˆ˜ ์žˆ๊ณ  ์ถฉ๋ถ„ํ•œ ๊ฐ€์šฉ ๋ Œ์น˜๊ณต๊ฐ„์„ ๊ฐ€์ง„ ๋งํฌ ๋ชจ๋“ˆ, 2) ๋†’์€ ์ž์œ ๋„์˜ ๋‹ค๊ด€์ ˆ๊ตฌ์กฐ ์‹œ์Šคํ…œ์„ ์œ„ํ•œ ์œ„์น˜ ๋ฐ ์ž์„ธ ์ถ”์ • ์•Œ๊ณ ๋ฆฌ์ฆ˜, 3) ์ž์—ฐ์Šค๋Ÿฌ์šด ์›€์ง์ž„์„ ๋‚ด๋Š” ๋™์‹œ์— ์ „์ฒด ์‹œ์Šคํ…œ์ด ์†๋„, ๊ฐ์†๋„ ๋“ฑ ์›ํ•˜๋Š” ์›€์ง์ž„์„ ๋‚ด๋„๋ก ํ•  ์ˆ˜ ์žˆ๋Š” ๋ชจ์…˜ ์ƒ์„ฑ ํ”„๋ ˆ์ž„์›Œํฌ๋กœ ๊ตฌ์„ฑ๋œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์šฐ์„  ๋งํฌ ๋ชจ๋“ˆ์˜ ๋””์ž์ธ์„ ์œ„ํ•ด ์ „๋ฐฉํ–ฅ์œผ๋กœ ๋ณด์žฅ๋˜๋Š” ํž˜๊ณผ ํ† ํฌ์˜ ํฌ๊ธฐ๋ฅผ ์ตœ๋Œ€ํ™”ํ•˜๋Š” ๊ตฌ์† ์ตœ์ ํ™”๋ฅผ ์‚ฌ์šฉํ•˜๊ณ , ์‹ค์ œ ์ ์šฉ๊ฐ€๋Šฅํ•œ ํ•ด๋ฅผ ์–ป๊ธฐ ์œ„ํ•ด ๋ช‡๊ฐ€์ง€ ๊ตฌ์†์กฐ๊ฑด(๋กœํ„ฐ ๊ฐ„ ๊ณต๊ธฐ ํ๋ฆ„ ๊ฐ„์„ญ์˜ ํšŒํ”ผ ๋“ฑ)์„ ๊ณ ๋ คํ•œ๋‹ค. ๋˜ํ•œ ์„ผ์„œ๊ฐ€ ์—†๋Š” ์•ก์ธ„์—์ดํ„ฐ๋กœ ์–‘๋ฐฉํ–ฅ ์ถ”๋ ฅ์„ ๋‚ด๋Š” ๊ฒƒ์—์„œ ์•ผ๊ธฐ๋˜๋Š” ESC ์œ ๋ฐœ ํŠน์ด์  (ESC-induced singularity) ์ด๋ผ๋Š” ๋ฌธ์ œ๋ฅผ ์ฒ˜์Œ์œผ๋กœ ์†Œ๊ฐœํ•˜๊ณ , ์ด๋ฅผ ํ•ด๊ฒฐํ•˜๊ธฐ ์œ„ํ•ด ์„ ํƒ์  ๋งตํ•‘ (selective mapping) ์ด๋ผ๋Š” ๊ธฐ๋ฒ•์„ ์ œ์‹œํ•œ๋‹ค. ์ „์ฒด LASDRA ์‹œ์Šคํ…œ์˜ ์ƒํƒœ์ถ”์ •์„ ์œ„ํ•ด ์‹œ์Šคํ…œ์˜ ๊ธฐ๊ตฌํ•™์  ๊ตฌ์†์กฐ๊ฑด์„ ๋งŒ์กฑํ•˜๋Š” ๊ฒฐ๊ณผ๋ฅผ ์–ป์„ ์ˆ˜ ์žˆ๋„๋ก ๊ตฌ์† ์นผ๋งŒ ํ•„ํ„ฐ ๊ธฐ๋ฐ˜์˜ ์ƒํƒœ์ถ”์ • ๊ธฐ๋ฒ•์„ ์ œ์‹œํ•˜๊ณ , ์‹œ์Šคํ…œ ํ™•์žฅ์„ฑ์„ ๊ณ ๋ คํ•˜์—ฌ ๋ฐ˜ ๋ถ„์‚ฐ (semi-distributed) ๊ฐœ๋…์˜ ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ํ•จ๊ป˜ ์ œ์‹œํ•œ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์ž์—ฐ์Šค๋Ÿฌ์šด ์›€์ง์ž„์˜ ์ƒ์„ฑ์„ ์œ„ํ•˜์—ฌ CPG ๊ธฐ๋ฐ˜์˜ ๋ชจ์…˜ ์ƒ์„ฑ ํ”„๋ ˆ์ž„์›Œํฌ๋ฅผ ์ œ์•ˆํ•˜๋ฉฐ, ๊ธฐ๊ณ„ ํ•™์Šต ๋ฐฉ๋ฒ•์„ ํ†ตํ•ด CPG ์—ญ์—ฐ์‚ฐ ๋ชจ๋ธ์„ ์–ป์Œ์œผ๋กœ์จ ์ „์ฒด ์‹œ์Šคํ…œ์ด ์›ํ•˜๋Š” ์›€์ง์ž„์„ ๋‚ผ ์ˆ˜ ์žˆ๋„๋ก ํ•œ๋‹ค.1 Introduction 1 1.1 Motivation and Background 1 1.2 Research Problems and Approach 3 1.3 Preview of Contributions 5 2 Omni-Directional Aerial Robot 7 2.1 Introduction 7 2.2 Mechanical Design 12 2.2.1 Design Description 12 2.2.2 Wrench-Maximizing Design Optimization 13 2.3 System Modeling and Control Design 20 2.3.1 System Modeling 20 2.3.2 Pose Trajectory Tracking Control 22 2.3.3 Hybrid Pose/Wrench Control 22 2.3.4 PSPM-Based Teleoperation 24 2.4 Control Allocation with Selective Mapping 27 2.4.1 Infinity-Norm Minimization 27 2.4.2 ESC-Induced Singularity and Selective Mapping 29 2.5 Experiment 38 2.5.1 System Setup 38 2.5.2 Experiment Results 41 2.6 Conclusion 49 3 Pose and Posture Estimation of an Aerial Skeleton System 51 3.1 Introduction 51 3.2 Preliminary 53 3.3 Pose and Posture Estimation 55 3.3.1 Estimation Algorithm via SCKF 55 3.3.2 Semi-Distributed Version of Algorithm 59 3.4 Simulation 62 3.5 Experiment 65 3.5.1 System Setup 65 3.5.2 Experiment of SCKF-Based Estimation Algorithm 66 3.6 Conclusion 69 4 CPG-Based Motion Generation 71 4.1 Introduction 71 4.2 Description of Entire Framework 75 4.2.1 LASDRA System 75 4.2.2 Snake-Like Robot & Pivotboard 77 4.3 CPG Model 79 4.3.1 LASDRA System 79 4.3.2 Snake-Like Robot 80 4.3.3 Pivotboard 83 4.4 Target Pose Calculation with Expected Physics 84 4.5 Inverse Model Learning 86 4.5.1 LASDRA System 86 4.5.2 Snake-Like Robot 89 4.5.3 Pivotboard 90 4.6 CPG Parameter Adaptation 93 4.7 Simulation 94 4.7.1 LASDRA System 94 4.7.2 Snake-Like Robot & Pivotboard 97 4.8 Conclusion 101 5 Outdoor Flight Experiment of the F-LASDRA System 103 5.1 System Setup 103 5.2 Experiment Results 104 6 Conclusion 111 6.1 Summary 111 6.2 Future Works 112Docto

    Intelligent approaches in locomotion - a review

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