Perspective for soft robotics: the field’s past and future

Tauber, Falk; Desmulliez, Marc Phillipe Yves; Piccin, Olivier; Stokes, Adam A.

doi:10.1088/1748-3190/acbb48

Cited by 25 publications

(5 citation statements)

References 99 publications

(128 reference statements)

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“…Future work will focus on deriving a more comprehensive framework in which co-contraction and feedback gains are concurrently planned, taking into account the consequences of noise/delays on state estimation and feedback control with respect to the task at hand. This framework could be applied to the development of soft robot control [61] and variable impedance actuators [62], and more generally to human-robot interaction towards health and manufacturing applications [63].…”

Section: Discussionmentioning

confidence: 99%

Co-Contraction Embodies Uncertainty: An Optimal Feedforward Strategy for Robust Motor Control

Berret,

Verdel,

Burdet

et al. 2024

Preprint

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Despite our environment is often uncertain, we generally manage to generate stable motor behaviors. While reactive control plays a major role in this achievement, proactive control is critical to cope with the substantial noise and delays that affect neuromusculoskeletal systems. In particular, muscle co-contraction is exploited to robustify feedforward motor commands against internal sensorimotor noise as was revealed by stochastic optimal open-loop control modeling. Here, we extend this framework to neuromusculoskeletal systems subjected to random disturbances originating from the environment. The analytical derivation and numerical simulations predict a singular relationship between the degree of uncertainty in the task at hand and the optimal level of anticipatory co-contraction. This prediction is confirmed through a single-joint pointing task experiment where an external torque is applied to the wrist near the end of the reaching movement with varying probabilities across blocks of trials. We conclude that uncertainty calls for impedance control via proactive muscle co-contraction to stabilize behaviors when reactive control is insufficient for task success.Author summaryThis work presents a computational framework for predicting how humans modulate muscle co-contraction to cope with uncertainties of different origins. In our neuromusculoskeletal system, uncertainties have both internal (sensorimotor noise) and external (environmental randomness) origins. The present study focuses on the latter type of uncertainty, which had not been dealt with systematically previously despite its importance in everyday life. Therefore, we thoroughly investigated how random disturbances occurring with some probability in a motor task shape the feedforward control of mechanical impedance through muscle co-contraction. Here we provide theoretical, numerical and experimental evidence that the optimal level of co-contraction steeply increases with the uncertainty of our environment. These findings show that muscle co-contraction embodies uncertainty and optimally mitigates its consequences on task execution when feedback control is insufficient due to sensory noise and delays.

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Section: Discussionmentioning

confidence: 99%

Co-Contraction Embodies Uncertainty: An Optimal Feedforward Strategy for Robust Motor Control

Berret,

Verdel,

Burdet

et al. 2024

Preprint

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“…While rigid robotic technologies excel in conventional tasks, they grapple with the demands of intricate and unstructured environments. Addressing these limitations and improving human-machine interaction safety, extensive attention has been directed towards the realm of soft actuators [1,2]. Soft robots, crafted from pliable materials, embody notable attributes including compliance, safety, and inherent adaptability [3,4].…”

Section: Introductionmentioning

confidence: 99%

Kinematics, dynamics and control of stiffness-tunable soft robots

Liu,

Xu,

Sui

et al. 2024

Bioinspir. Biomim.

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Modeling and control methods for stiffness-tunable soft robots (STSRs) have received less attention compared to standard soft robots. A major challenge in controlling STSRs is their infinite degrees of freedom, similar to standard soft robots. In this paper, demonstrate a novel stiffness-tunable soft robot by combing a soft-rigid hybrid spine-mimicking actuator with a stiffness-tunable module. Additionally, we introduce a new kinematic and dynamic modeling methodology for the proposed STSR. Based on the STSR characteristics, we model it as a series of PRP segments, each composed of two prismatic joints(P) and one revolute joint(R). This method is simpler, more generalizable, and more computationally efficient than existing approaches. We also design a multi-input multi-output (MIMO) controller that directly adjusts the pressure of the STSR's three pneumatic chambers to precisely control its posture. Both the novel modeling methodology and MIMO control system are implemented and validated on the proposed STSR prototype.

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“…Bioinspired and biomimetic soft robotics are significantly changing the field of robotics research. Researchers are studying how various mechanisms have evolved in nature, aiming to mimic the adaptability and versatility of biological systems without necessarily replicating their exact structure [1][2][3][4]. Such robots aim to impersonate a variety of functions from the animal and plant kingdom, including the suction capabilities of octopus suction cups [5][6][7], the adhesive properties of gecko feet [8], the movement of octopus tentacles [9][10][11], the grasping mechanism found in bird claws [12], the walking gait of insects [13], or the snapping mechanism of the Venus flytrap [14,15].…”

Section: Introductionmentioning

confidence: 99%

Soft octopus-inspired suction cups using dielectric elastomer actuators with sensing capabilities

Jamali,

Mishra,

Goldschmidtboeing

et al. 2024

Bioinspir. Biomim.

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Bioinspired and biomimetic soft grippers are rapidly growing fields. They represent an advancement in soft robotics as they emulate the adaptability and flexibility of biological end effectors. A prominent example of a gripping mechanism found in nature is the octopus tentacle, enabling the animal to attach to rough and irregular surfaces. Inspired by the structure and morphology of the tentacles, this study introduces a novel design, fabrication and characterization method of dielectric elastomer suction cups. To grasp objects, the developed suction cups perform out-of-plane deflections as the suction mechanism. Their attachment mechanism resembles that of their biological counterparts, as they do not require a pre-stretch over a rigid frame or any external hydraulic or pneumatic support to form and hold the dome structure of the suction cups. The realized artificial suction cups demonstrate the capability of generating a negative pressure up to 1.3 kPa in air and grasping and lifting objects with a maximum 58 g weight under an actuation voltage of 6 kV. They also have sensing capabilities to determine whether the grasping was successful without the need of lifting the objects.

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Perspective for soft robotics: the field’s past and future

Cited by 25 publications

References 99 publications

Co-Contraction Embodies Uncertainty: An Optimal Feedforward Strategy for Robust Motor Control

Co-Contraction Embodies Uncertainty: An Optimal Feedforward Strategy for Robust Motor Control

Kinematics, dynamics and control of stiffness-tunable soft robots

Soft octopus-inspired suction cups using dielectric elastomer actuators with sensing capabilities

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