Variable impedance actuators: Moving the robots of tomorrow

Vanderborght, Bram; Bicchi, Antonio; Burdet, Etienne; Caldwell, Darwin G.; Carloni, Raffaella; Catalano, Manuel G.; Ganesh, Gowrishankar; Garabini, Manolo; Grebenstein, Markus; Haddadin, Sami; Laffranchi, Matteo; Lefeber, Dirk; Petit, Florian; Tsagarakis, Nikos G.; Damme, Michaël Van; Ham, Ronald Van; Visser, Ludo C.; Wolf, Sebastian

doi:10.1109/iros.2012.6385433

Cited by 40 publications

(28 citation statements)

References 28 publications

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“…As far as motor planning is of concern and the elaboration of feedforward motor commands is thought to be a significant component of the neural control of movement (see also [84]), the SOOC theory may constitute a relevant theoretical approach. At last, we note that the very same framework could prove useful in human-inspired robotics especially for robots with variable impedance actuators [45,85].…”

Section: Resultsmentioning

confidence: 88%

“…Although we use the term open-loop -in the sense of control theory-we do not necessarily exclude the role of automatic short-latency reflexes that contribute to the spring-like behavior of intact muscles beyond their short-range stiffness. However, we do exclude from this open-loop terminology all the optimal feedback control processes integrating sensory data during movement execution through 85 transcortical feedback loops [31]. The critical role of SOFC is rather attributed to those long-latency, sophisticated and task-dependent motor responses that are triggered by the CNS to correct large-enough external perturbations [32,33].…”

Section: Introductionmentioning

confidence: 99%

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Stochastic optimal open-loop control as a theory of force and impedance planning via muscle co-contraction

Berret

Jean

2019

Preprint

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Understanding the underpinnings of biological motor control is an important issue in movement neuroscience. Optimal control theory is a leading framework to rationalize this problem in computational terms. Previously, optimal control models have been devised either in deterministic or in stochastic settings to account for different aspects of motor control (e.g. average behavior versus trial-to-trial variability). While these approaches have yielded valuable insights about motor control, they typically fail explain a common phenomenon known as muscle co-contraction. Co-contraction of agonist and antagonist muscles contributes to modulate the mechanical impedance of the neuromusculoskeletal system (e.g. joint stiffness) and is thought to be mainly under the influence of descending signals from the brain.Here we present a theory suggesting that one primary goal of motor planning may be to issue feedforward (open-loop) motor commands that optimally specify both force and impedance, according to the noisy neuromusculoskeletal dynamics and to optimality criteria based on effort and variance. We show that the proposed framework naturally accounts for several previous experimental findings regarding the regulation of force and impedance via muscle co-contraction in the upper-limb. Optimal feedback (closedloop) control, preprogramming feedback gains but requiring on-line state estimation processes through long-latency sensory feedback loops, may then complement this nominal feedforward motor command to fully determine the limb's mechanical impedance. The stochastic optimal open-loop control theory may provide new insights about the general articulation of feedforward/feedback control mechanisms and justify the occurrence of muscle co-contraction in the neural control of movement. Author summaryThis study presents a novel computational theory to explain the planning of force and impedance (e.g. stiffness) in the neural control of movement. It assumes that one main goal of motor planning is to elaborate feedforward motor commands that determine both the force and the impedance required for the task at hand. These feedforward motor commands (i.e. that are defined prior to movement execution) are designed to minimize effort and variance costs considering the uncertainty arising from sensorimotor noise. A major outcome of this mathematical framework is the explanation of a long-known phenomenon called muscle co-contraction (i.e. the concurrent contraction of opposing muscles). Muscle co-contraction has been shown to occur in many situations but previous modeling works struggled to account for it.Although effortful, co-contraction contributes to increase the robustness of motor behavior (e.g. small variance) upstream of sophisticated optimal feedback control processes that require state estimation from delayed sensory feedback to function. This work may have implications regarding our understanding of the neural control of movement in computational terms. It also provides a theoretical ground to explain how to optimally plan f...

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Section: Resultsmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Stochastic optimal open-loop control as a theory of force and impedance planning via muscle co-contraction

Berret

Jean

2019

Preprint

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“…One potential solution to this dilemma is using a variable stiffness actuator or structure such as [18]. While a number of interesting designs for variable impedance actuators and joints have appeared in the literature, both of these approaches greatly increase complexity and cost due to the sensing, motors, and mechanisms required.…”

Section: Discussionmentioning

confidence: 99%

Limits to compliance and the role of tactile sensing in grasping

Jentoft

Wan

Howe

2014

2014 IEEE International Conference on Robotics and Automation (ICRA)

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Grasping and manipulation in unstructured environments must handle a wide range of object properties and significant sensing errors. Underactuation and compliance have been shown to be an effective way to improve grasping performance under such uncertainty, but the degree of compliance plays an important role in both gently adapting to sensing errors and maintaining stable grasps of heavy objects. These demands limit the range of objects that can be grasped. We consider the role and required characteristics of tactile sensing as a compensation method when compliance alone is insufficient. By strategic use of contact sensing, it is possible to expand the capabilities of a hand to grasp effectively under a wide range of positioning errors using simple position-driven motors and low-cost hardware.

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“…Możliwość płynnej regulacji podatności, w połączeniu z odpowiednim algorytmem sterowania, może przynieść szereg innych wymiernych korzyści -począwszy od zmniejszenia zużycia energii w trakcie powtarzalnych czynności manipulatora przemysłowego, a skończywszy na płynnym chodzie w przypadku robotów kroczących [1].…”

Section: Wprowadzenieunclassified

“…Poniżej przedstawiono jej zalety i wady. 1 Jeżeli np. regulacja sztywności odbywa się przez zmianę napięcia wstępnego sprężyn, to warunek 100% sprawności procesu oznacza, że cała energia dostarczana do mechanizmu zmiany sztywności zamieniana jest w energię odkształ-cenia sprężyn -energia nie jest dyssypowana.…”

Section: ǣɩ ăǜř˹˿ ʊ˘ǜ˿˹ȭƭ ˘ ɡɂƞřǜȭɂʋƌǔŭ ɂʊǔŭƿřȭŭ Przez Sterowanieunclassified

Classification of Variable Stiffness Actuators - part 1

Kozakiewicz¹,

Winiarski²

2017

PAR

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ŎƬ˘˹ŘǚŘ ʊǔǄ ȭŘ ǘɁʁ˘˿ʊǜŘȭǔƬ ˘ Řʁǜ˿ǘˁȦˁ ȭŘ ˹ŘʁˁȭǘŘƋǒ ǚǔƋƬȭƋǖǔ ,ʁƬŘǜǔ˸Ƭ ,ɁȧȧɁȭʊ Ę˘ȭŘȭǔƬ ŘˁǜɁʁʊǜ˹Ř ʯƖ1 . WprowadzenieWiększość aktualnie stosowanych manipulatorów stanowią mechanizmy sztywne, sterowane pozycyjnie. Tego typu układy zapewniają dużą precyzję ruchów, ale stanowią znaczne zagrożenie dla wszelkich obiektów, które nieoczekiwanie znajdą się w przestrzeni roboczej robota -w szczególności dla ludzi.Niebezpieczeństwo to można zmniejszyć przez wprowadzenie podatności do przegubów robota. Zabieg ten nie tylko redukuje skutki zderzenia z przeszkodą (korzystnie wpływając na możliwość bezpośredniej współpracy robota z człowiekiem), ale pozwala również magazynować energię.Możliwość płynnej regulacji podatności, w połączeniu z odpowiednim algorytmem sterowania, może przynieść szereg innych wymiernych korzyści -począwszy od zmniejszenia zużycia energii w trakcie powtarzalnych czynności manipulatora przemysłowego, a skończywszy na płynnym chodzie w przypadku robotów kroczących [1].

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Variable impedance actuators: Moving the robots of tomorrow

Cited by 40 publications

References 28 publications

Stochastic optimal open-loop control as a theory of force and impedance planning via muscle co-contraction

Stochastic optimal open-loop control as a theory of force and impedance planning via muscle co-contraction

Limits to compliance and the role of tactile sensing in grasping

Classification of Variable Stiffness Actuators - part 1

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