269 research outputs found

    Multisensor Input for CPG-Based Sensoryโ€”Motor Coordination

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    International audienceThis paper describes a method for providing in real time a reliable synchronization signal for cyclical motions such as steady-state walking. The approach consists in estimating online a phase variable on the basis of several implicit central pattern generator associated with a set of sensors. These sensors can be of any kind, provided their output strongly reflects the timedmotion of a link. They can be, for example, spatial position or orientation sensors, or foot sole pressure sensors. The principle of the method is to use their outputs as inputs to nonlinear observers of modified Van der Pol oscillators that provide us with several independent estimations of the overall phase of the system. These estimations are then combined within a dynamical filter constituted of a Hopf oscillator. The resulting phase is a reliable indexing of the cyclic behavior of the system, which can finally be used as input to low-level controllers of a robot. Some results illustrate the efficiency of the approach, which can be used to control robots

    Contact-Aided Invariant Extended Kalman Filtering for Legged Robot State Estimation

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    This paper derives a contact-aided inertial navigation observer for a 3D bipedal robot using the theory of invariant observer design. Aided inertial navigation is fundamentally a nonlinear observer design problem; thus, current solutions are based on approximations of the system dynamics, such as an Extended Kalman Filter (EKF), which uses a system's Jacobian linearization along the current best estimate of its trajectory. On the basis of the theory of invariant observer design by Barrau and Bonnabel, and in particular, the Invariant EKF (InEKF), we show that the error dynamics of the point contact-inertial system follows a log-linear autonomous differential equation; hence, the observable state variables can be rendered convergent with a domain of attraction that is independent of the system's trajectory. Due to the log-linear form of the error dynamics, it is not necessary to perform a nonlinear observability analysis to show that when using an Inertial Measurement Unit (IMU) and contact sensors, the absolute position of the robot and a rotation about the gravity vector (yaw) are unobservable. We further augment the state of the developed InEKF with IMU biases, as the online estimation of these parameters has a crucial impact on system performance. We evaluate the convergence of the proposed system with the commonly used quaternion-based EKF observer using a Monte-Carlo simulation. In addition, our experimental evaluation using a Cassie-series bipedal robot shows that the contact-aided InEKF provides better performance in comparison with the quaternion-based EKF as a result of exploiting symmetries present in the system dynamics.Comment: Published in the proceedings of Robotics: Science and Systems 201

    Humanoid Robots

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    For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

    Review of Anthropomorphic Head Stabilisation and Verticality Estimation in Robots

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    International audienceIn many walking, running, flying, and swimming animals, including mammals, reptiles, and birds, the vestibular system plays a central role for verticality estimation and is often associated with a head sta-bilisation (in rotation) behaviour. Head stabilisation, in turn, subserves gaze stabilisation, postural control, visual-vestibular information fusion and spatial awareness via the active establishment of a quasi-inertial frame of reference. Head stabilisation helps animals to cope with the computational consequences of angular movements that complicate the reliable estimation of the vertical direction. We suggest that this strategy could also benefit free-moving robotic systems, such as locomoting humanoid robots, which are typically equipped with inertial measurements units. Free-moving robotic systems could gain the full benefits of inertial measurements if the measurement units are placed on independently orientable platforms, such as a human-like heads. We illustrate these benefits by analysing recent humanoid robots design and control approaches

    ์™ธ๋ž€ ๋ฐ ํ† ํฌ ๋Œ€์—ญํญ ์ œํ•œ์„ ๊ณ ๋ คํ•œ ํ† ํฌ ๊ธฐ๋ฐ˜์˜ ์ž‘์—… ๊ณต๊ฐ„ ์ œ์–ด

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์œตํ•ฉ๊ณผํ•™๊ธฐ์ˆ ๋Œ€ํ•™์› ์œตํ•ฉ๊ณผํ•™๋ถ€(์ง€๋Šฅํ˜•์œตํ•ฉ์‹œ์Šคํ…œ์ „๊ณต), 2021.8. ๋ฐ•์žฌํฅ.The thesis aims to improve the control performance of the torque-based operational space controller under disturbance and torque bandwidth limitation. Torque-based robot controllers command the desired torque as an input signal to the actuator. Since the torque is at force-level, the torque-controlled robot is more compliant to external forces from the environment or people than the position-controlled robot. Therefore, it can be used effectively for the tasks involving contact such as legged locomotion or human-robot interaction. Operational space control strengthens this advantage for redundant robots due to the inherent compliance in the null space of given tasks. However, high-level torque-based controllers have not been widely used for transitional robots such as industrial manipulators due to the low performance of precise control. One of the reasons is the uncertainty or disturbance in the kinematic and dynamic properties of the robot model. It leads to the inaccurate computation of the desired torque, deteriorating the control stability and performance. To estimate and compensate the disturbance using only proprioceptive sensors, the disturbance observer has been developed using inverse dynamics. It requires the joint acceleration information, which is noisy due to the numerical error in the second-order derivative of the joint position. In this work, a contact-consistent disturbance observer for a floating-base robot is proposed. The method uses the fixed contact position of the supporting foot as the kinematic constraints to estimate the joint acceleration error. It is incorporated into the dynamics model to reduce its effect on the disturbance torque solution, by which the observer becomes less dependent on the low-pass filter design. Another reason for the low performance of precise control is torque bandwidth limitation. Torque bandwidth is determined by the relationship between the input torque commanded to the actuator and the torque actually transmitted into the link. It can be regulated by various factors such as inner torque feedback loop, actuator dynamics, and joint elasticity, which deteriorates the control stability and performance. Operational space control is especially prone to this problem, since the limited bandwidth of a single actuator can reduce the performance of all related tasks simultaneously. In this work, an intuitive way to penalize low performance actuators is proposed for the operational space controller. The basic concept is to add joint torques only to high performance actuators recursively, which has the physical meaning of the joint-weighted torque solution considering each actuator performance. By penalizing the low performance actuators, the torque transmission error is reduced and the task performance is significantly improved. In addition, the joint trajectory is not required, which allows compliance in redundancy. The results of the thesis were verified by experiments using the 12-DOF biped robot DYROS-RED and the 7-DOF robot manipulator Franka Emika Panda.๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์€ ์™ธ๋ž€๊ณผ ํ† ํฌ ๋Œ€์—ญํญ ์ œํ•œ์ด ์กด์žฌํ•  ๋•Œ ํ† ํฌ ๊ธฐ๋ฐ˜ ์ž‘์—… ๊ณต๊ฐ„ ์ œ์–ด๊ธฐ์˜ ์ œ์–ด ์„ฑ๋Šฅ์„ ๋†’์ด๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•œ๋‹ค. ํ† ํฌ ๊ธฐ๋ฐ˜์˜ ๋กœ๋ด‡ ์ œ์–ด๊ธฐ๋Š” ๋ชฉํ‘œ ํ† ํฌ๋ฅผ ์ž…๋ ฅ ์‹ ํ˜ธ๋กœ์„œ ๊ตฌ๋™๊ธฐ์— ์ „๋‹ฌํ•œ๋‹ค. ํ† ํฌ๋Š” ํž˜ ๋ ˆ๋ฒจ์ด๊ธฐ ๋•Œ๋ฌธ์—, ํ† ํฌ ์ œ์–ด ๋กœ๋ด‡์€ ์œ„์น˜ ์ œ์–ด ๋กœ๋ด‡์— ๋น„ํ•ด ์™ธ๋ถ€ ํ™˜๊ฒฝ์ด๋‚˜ ์‚ฌ๋žŒ์œผ๋กœ๋ถ€ํ„ฐ ๊ฐ€ํ•ด์ง€๋Š” ์™ธ๋ ฅ์— ๋” ์œ ์—ฐํ•˜๊ฒŒ ๋Œ€์‘ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋ฏ€๋กœ ํ† ํฌ ์ œ์–ด๋Š” ๋ณดํ–‰์ด๋‚˜ ์ธ๊ฐ„-๋กœ๋ด‡ ์ƒํ˜ธ์ž‘์šฉ๊ณผ ๊ฐ™์€ ์ ‘์ด‰์„ ํฌํ•จํ•˜๋Š” ์ž‘์—…์„ ์œ„ํ•ด ํšจ๊ณผ์ ์œผ๋กœ ์‚ฌ์šฉ๋  ์ˆ˜ ์žˆ๋‹ค. ์ž‘์—… ๊ณต๊ฐ„ ์ œ์–ด๋Š” ์ด๋Ÿฌํ•œ ํ† ํฌ ์ œ์–ด์˜ ์žฅ์ ์„ ๋” ๊ฐ•ํ™”์‹œํ‚ฌ ์ˆ˜ ์žˆ๋Š”๋ฐ, ๋กœ๋ด‡์ด ์—ฌ์œ  ์ž์œ ๋„๊ฐ€ ์žˆ์„ ๋•Œ ์ž‘์—…์˜ ์˜๊ณต๊ฐ„์—์„œ ์กด์žฌํ•˜๋Š” ๋ชจ์…˜๋“ค์ด ๋‚ด์žฌ์ ์œผ๋กœ ์œ ์—ฐํ•˜๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋Ÿฌํ•œ ์žฅ์ ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ  ํ† ํฌ ๊ธฐ๋ฐ˜์˜ ๋กœ๋ด‡ ์ œ์–ด๊ธฐ๋Š” ์ •๋ฐ€ ์ œ์–ด ์„ฑ๋Šฅ์ด ๋–จ์–ด์ง€๊ธฐ ๋•Œ๋ฌธ์— ์‚ฐ์—…์šฉ ๋กœ๋ด‡ ํŒ”๊ณผ ๊ฐ™์€ ์ „ํ†ต์ ์ธ ๋กœ๋ด‡์—๋Š” ๋„๋ฆฌ ์‚ฌ์šฉ๋˜์ง€ ๋ชปํ–ˆ๋‹ค. ๊ทธ ์ด์œ  ์ค‘ ํ•œ ๊ฐ€์ง€๋Š” ๋กœ๋ด‡ ๋ชจ๋ธ์˜ ๊ธฐ๊ตฌํ•™ ๋ฐ ๋™์—ญํ•™ ๋ฌผ์„ฑ์น˜์— ์กด์žฌํ•˜๋Š” ์™ธ๋ž€์ด๋‹ค. ๋ชจ๋ธ ์˜ค์ฐจ๋Š” ๋ชฉํ‘œ ํ† ํฌ๋ฅผ ๊ณ„์‚ฐํ•  ๋•Œ ์˜ค์ฐจ๋ฅผ ์œ ๋ฐœํ•˜๋ฉฐ, ์ด๊ฒƒ์ด ์ œ์–ด ์•ˆ์ •์„ฑ๊ณผ ์„ฑ๋Šฅ์„ ์•ฝํ™”์‹œํ‚ค๊ฒŒ ๋œ๋‹ค. ์™ธ๋ž€์„ ๋‚ด์žฌ ์„ผ์„œ๋งŒ์„ ์ด์šฉํ•˜์—ฌ ์ถ”์ • ๋ฐ ๋ณด์ƒํ•˜๊ธฐ ์œ„ํ•ด ์—ญ๋™์—ญํ•™ ๊ธฐ๋ฐ˜์˜ ์™ธ๋ž€ ๊ด€์ธก๊ธฐ๊ฐ€ ๊ฐœ๋ฐœ๋˜์–ด ์™”๋‹ค. ์™ธ๋ž€ ๊ด€์ธก๊ธฐ๋Š” ์—ญ๋™์—ญํ•™ ๊ณ„์‚ฐ์„ ์œ„ํ•ด ๊ด€์ ˆ ๊ฐ๊ฐ€์†๋„ ์ •๋ณด๊ฐ€ ํ•„์š”ํ•œ๋ฐ, ์ด ๊ฐ’์ด ๊ด€์ ˆ ์œ„์น˜๋ฅผ ๋‘ ๋ฒˆ ๋ฏธ๋ถ„ํ•œ ๊ฐ’์ด๊ธฐ ๋•Œ๋ฌธ์— ์ˆ˜์น˜์ ์ธ ์˜ค์ฐจ๋กœ ๋…ธ์ด์ฆˆํ•ด์ง€๋Š” ๋ฌธ์ œ๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋ถ€์œ ํ˜• ๊ธฐ์ € ๋กœ๋ด‡์„ ์œ„ํ•œ ์ ‘์ด‰ ์กฐ๊ฑด์ด ๊ณ ๋ ค๋œ ์™ธ๋ž€ ๊ด€์ธก๊ธฐ๊ฐ€ ์ œ์•ˆ๋˜์—ˆ๋‹ค. ์ œ์•ˆ๋œ ๋ฐฉ๋ฒ•์€ ๋กœ๋ด‡์˜ ๊ณ ์ •๋œ ์ ‘์ด‰ ์ง€์ ์— ๋Œ€ํ•œ ๊ธฐ๊ตฌํ•™์ ์ธ ๊ตฌ์† ์กฐ๊ฑด์„ ์ด์šฉํ•˜์—ฌ ๊ด€์ ˆ ๊ฐ๊ฐ€์†๋„ ์˜ค์ฐจ๋ฅผ ์ถ”์ •ํ•œ๋‹ค. ์ถ”์ •๋œ ์˜ค์ฐจ๋ฅผ ๋™์—ญํ•™ ๋ชจ๋ธ์— ๋ฐ˜์˜ํ•˜์—ฌ ์™ธ๋ž€ ํ† ํฌ๋ฅผ ๊ณ„์‚ฐํ•จ์œผ๋กœ์จ ์ €์—ญ ํ†ต๊ณผ ํ•„ํ„ฐ ์„ฑ๋Šฅ์— ๋Œ€ํ•œ ์˜์กด๋„๋ฅผ ์ค„์ผ ์ˆ˜ ์žˆ๋‹ค. ํ† ํฌ ๊ธฐ๋ฐ˜ ์ œ์–ด์˜ ์ •๋ฐ€ ์ œ์–ด ์„ฑ๋Šฅ์ด ๋–จ์–ด์ง€๋Š” ๋˜ ๋‹ค๋ฅธ ์ด์œ  ์ค‘ ํ•˜๋‚˜๋Š” ํ† ํฌ ๋Œ€์—ญํญ ์ œํ•œ์ด๋‹ค. ํ† ํฌ ๋Œ€์—ญํญ์€ ๊ตฌ๋™๊ธฐ์— ์ „๋‹ฌ๋˜๋Š” ์ž…๋ ฅ ํ† ํฌ์™€ ์‹ค์ œ ๋งํฌ์— ์ „๋‹ฌ๋˜๋Š” ํ† ํฌ์™€์˜ ๊ด€๊ณ„๋กœ ๊ฒฐ์ •๋œ๋‹ค. ํ† ํฌ ๋Œ€์—ญํญ์€ ๊ตฌ๋™๊ธฐ ๋‚ด๋ถ€์˜ ํ† ํฌ ํ”ผ๋“œ๋ฐฑ ๋ฃจํ”„, ๊ตฌ๋™๊ธฐ ๋™์—ญํ•™, ๊ด€์ ˆ ํƒ„์„ฑ ๋“ฑ์˜ ์š”์ธ๋“ค์— ์˜ํ•ด ์ œํ•œ๋  ์ˆ˜ ์žˆ๋Š”๋ฐ ์ด๊ฒƒ์ด ์ œ์–ด ์•ˆ์ •์„ฑ ๋ฐ ์„ฑ๋Šฅ์„ ๊ฐ์†Œ์‹œํ‚จ๋‹ค. ์ž‘์—… ๊ณต๊ฐ„ ์ œ์–ด๋Š” ํŠนํžˆ ์ด ๋ฌธ์ œ์— ์ทจ์•ฝํ•œ๋ฐ, ๋Œ€์—ญํญ์ด ์ œํ•œ๋œ ๊ตฌ๋™๊ธฐ ํ•˜๋‚˜๊ฐ€ ๊ทธ์™€ ์—ฐ๊ด€๋œ ๋ชจ๋“  ์ž‘์—… ๊ณต๊ฐ„์˜ ์ œ์–ด ์„ฑ๋Šฅ์„ ๊ฐ์†Œ์‹œํ‚ฌ ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ์ž‘์—… ๊ณต๊ฐ„ ์ œ์–ด๊ธฐ์—์„œ ์„ฑ๋Šฅ์ด ๋‚ฎ์€ ๊ตฌ๋™๊ธฐ์˜ ์‚ฌ์šฉ์„ ์ œํ•œํ•˜๊ธฐ ์œ„ํ•œ ์ง๊ด€์ ์ธ ์ „๋žต์ด ์ œ์•ˆ๋˜์—ˆ๋‹ค. ๊ธฐ๋ณธ ์ปจ์…‰์€ ์ž‘์—… ์ œ์–ด๋ฅผ ์œ„ํ•œ ํ† ํฌ ์†”๋ฃจ์…˜์— ์„ฑ๋Šฅ์ด ์ข‹์€ ๊ด€์ ˆ์—๋งŒ ์ถ”๊ฐ€์ ์œผ๋กœ ํ† ํฌ ์†”๋ฃจ์…˜์„ ๋”ํ•ด๋‚˜๊ฐ€๋Š” ๊ฒƒ์œผ๋กœ, ์ด๊ฒƒ์€ ๊ฐ ๊ด€์ ˆ์˜ ๊ฐ€์ค‘์น˜๊ฐ€ ๊ณ ๋ ค๋œ ํ† ํฌ ์†”๋ฃจ์…˜์ด ๋˜๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•œ๋‹ค. ์„ฑ๋Šฅ์ด ๋‚ฎ์€ ๊ตฌ๋™๊ธฐ์˜ ์‚ฌ์šฉ์„ ์ œํ•œํ•จ์œผ๋กœ์จ ํ† ํฌ ์ „๋‹ฌ ์˜ค์ฐจ๊ฐ€ ์ค„์–ด๋“ค๊ณ  ์ž‘์—… ์„ฑ๋Šฅ์ด ํฌ๊ฒŒ ํ–ฅ์ƒ๋  ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ํ•™์œ„ ๋…ผ๋ฌธ์˜ ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋“ค์€ 12์ž์œ ๋„ ์ด์กฑ ๋ณดํ–‰ ๋กœ๋ด‡ DYROS-RED์™€ 7์ž์œ ๋„ ๋กœ๋ด‡ ํŒ” Franka Emika Panda๋ฅผ ์ด์šฉํ•œ ์‹คํ—˜์„ ํ†ตํ•ด ๊ฒ€์ฆ๋˜์—ˆ๋‹ค.1 INTRODUCTION 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Contributions of Thesis . . . . . . . . . . . . . . . . . . . . . . . 4 1.3 Overview of Thesis . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 BACKGROUNDS 6 2.1 Operational Space Control . . . . . . . . . . . . . . . . . . . . . . 6 2.2 Dynamics Formulation . . . . . . . . . . . . . . . . . . . . . . . . 9 2.2.1 Fixed-Base Dynamics . . . . . . . . . . . . . . . . . . . . 9 2.2.1.1 Joint Space Formulation . . . . . . . . . . . . . 9 2.2.1.2 Operational Space Formulation . . . . . . . . . . 11 2.2.2 Floating-Base Dynamics . . . . . . . . . . . . . . . . . . . 12 2.2.2.1 Joint Space Formulation . . . . . . . . . . . . . 12 2.2.2.2 Operational Space Formulation . . . . . . . . . . 14 2.3 Position Tracking via PD Control . . . . . . . . . . . . . . . . . . 17 2.3.1 Torque Solution . . . . . . . . . . . . . . . . . . . . . . . 17 2.3.2 Orientation Control . . . . . . . . . . . . . . . . . . . . . 19 3 CONTACT-CONSISTENT DISTURBANCE OBSERVER FOR FLOATING-BASE ROBOTS 22 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.2 Momentum-Based Disturbance Observer . . . . . . . . . . . . . . 24 3.3 The Proposed Method . . . . . . . . . . . . . . . . . . . . . . . . 25 3.4 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.4.1 Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.4.2 External Force Estimation . . . . . . . . . . . . . . . . . . 33 3.4.3 Internal Disturbance Rejection . . . . . . . . . . . . . . . 35 3.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 4 OPERATIONAL SPACE CONTROL UNDER ACTUATOR BANDWIDTH LIMITATION 40 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 4.2 The Proposed Method . . . . . . . . . . . . . . . . . . . . . . . . 43 4.2.1 General Concepts . . . . . . . . . . . . . . . . . . . . . . . 43 4.2.2 OSF-Based Torque Solution . . . . . . . . . . . . . . . . . 45 4.2.3 Comparison With a Typical Method . . . . . . . . . . . . 47 4.3 Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.3.1 Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.3.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 4.4 Comparison With Other Approaches . . . . . . . . . . . . . . . . 61 4.4.1 Controller Formulation . . . . . . . . . . . . . . . . . . . . 62 4.4.1.1 The Proposed Method . . . . . . . . . . . . . . . 62 4.4.1.2 The OSF Controller . . . . . . . . . . . . . . . . 62 4.4.1.3 The OSF-Filter Controller . . . . . . . . . . . . 62 4.4.1.4 The OSF-Joint Controller . . . . . . . . . . . . . 67 4.4.1.5 The Joint Controller . . . . . . . . . . . . . . . . 68 4.4.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 4.5 Frequency Response of Joint Torque . . . . . . . . . . . . . . . . 72 4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83 5 CONCLUSION 85 Abstract (In Korean) 100๋ฐ•

    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
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