Series pneumatic artificial muscles (sPAMs) and application to a soft continuum robot

Greer, Joseph D.; Morimoto, Tania K.; Okamura, Allison M.; Hawkes, Elliot W.

doi:10.1109/icra.2017.7989648

Cited by 145 publications

(106 citation statements)

References 23 publications

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“…We demonstrate this by using a CFR to control a pair of reverse-polarity LEDs ( Figure S1A, Supplementary movie S8) and to switch both a shape-memory alloy (SMA) actuator ( Figure S1B) and a low-boiling point fluid pouch motor ( Figure S1C). These results show that the CFR is suitable for the control of a wide range of soft robotic systems (7,21,33,62,77).…”

Section: The Soft Matter Computermentioning

confidence: 72%

A soft matter computer for soft robots

et al. 2019

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Despite the growing interest in soft robotics, little attention has been paid to the development of soft matter computational mechanisms. Embedding computation directly into soft materials is not only necessary for the next generation of fully soft robots but also for smart materials to move beyond stimulus-response relationships and toward the intelligent behaviors seen in biological systems. This article describes soft matter computers (SMCs), low-cost, and easily fabricated computational mechanisms for soft robots. The building block of an SMC is a conductive fluid receptor (CFR), which maps a fluidic input signal to an electrical output signal via electrodes embedded into a soft tube. SMCs could perform both analog and digital computation. The potential of SMCs is demonstrated by integrating them into three soft robots: (i) a Softworm robot was controlled by an SMC that generated the control signals necessary for three distinct gaits; (ii) a soft gripper was given a set of reflexes that could be programmed by adjusting the parameters of the CFR; and (iii) a two–degree of freedom bending actuator was switched between three distinct behaviors by varying only one input parameter. SMCs are a low-cost way to integrate computation directly into soft materials and an important step toward entirely soft autonomous robots.

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Section: The Soft Matter Computermentioning

confidence: 72%

A soft matter computer for soft robots

et al. 2019

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“…In order to conduct the intricate manipulations required in the management of productive agroforestry systems, a gripping action is needed. Most continuum manipulators utilize a suction gripper at its tip to grip small objects [40,42]. If robot-mounted vacuum pumps are employed for vacuum-assisted stiffening, this may be a viable option.…”

Section: Design and Integration Of Soft Continuum Armsmentioning

confidence: 99%

“…Human demonstration of movement in these agroforestry tasks can be documented and used to provide initial guidance for enabling diverse tasks in complex field environments. It is challenging to design optimal controllers for continuum arms with traditional model-based control methods [42,51,65] due to the large numbers of degrees of freedom of continuum arms and the large number of pressure valves. These factors also make them notoriously difficult to control by humans.…”

Section: Autonomous Control With Learningmentioning

confidence: 99%

“…Leveraging the reward functions learned from experts, the robot can be taught optimal policies for executing multiple complex tasks. Given the complexity of continuum arm models and the very sparse literature that exists on the control of continuum arms [42,51,65], Reinforcement Learning emerges as a good approach to begin with, at least until the advances in this project lead to the discovery of new ways of controlling such arms. DRL policies will be applied for the control of continuum arms that are robust to real-world uncertainty using imperfect simulations.…”

Section: Autonomous Control With Learningmentioning

confidence: 99%

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Soft Robotics as an Enabling Technology for Agroforestry Practice and Research

Chowdhary

Gazzola²,

Krishnan³

et al. 2019

Sustainability

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The shortage of qualified human labor is a key challenge facing farmers, limiting profit margins and preventing the adoption of sustainable and diversified agroecosystems, such as agroforestry. New technologies in robotics could offer a solution to such limitations. Advances in soft arms and manipulators can enable agricultural robots that can have better reach and dexterity around plants than traditional robots equipped with hard industrial robotic arms. Soft robotic arms and manipulators can be far less expensive to manufacture and significantly lighter than their hard counterparts. Furthermore, they can be simpler to design and manufacture since they rely on fluidic pressurization as the primary mechanisms of operation. However, current soft robotic arms are difficult to design and control, slow to actuate, and have limited payloads. In this paper, we discuss the benefits and challenges of soft robotics technology and what it could mean for sustainable agriculture and agroforestry.

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“…Bending is achieved using series pneumatic artificial muscles (sPAMs) [17] that are attached along the length of the robot's body (Fig. 2).…”

Section: Introductionmentioning

confidence: 99%

A Soft, Steerable Continuum Robot That Grows via Tip Extension

et al. 2019

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Soft continuum robots exhibit access and manipulation capabilities in constrained and cluttered environments not achievable by traditional robots. However, environmental contact can drastically alter the motion of continuum robots, complicating their control in these applications. Here we describe the design, modeling, and control of a soft continuum robot with a novel extension degree-of-freedom that enables movement in a direction that is always tangent to the robot's backbone, independent of environmental contacts. Steering occurs by inflating multiple Series Pneumatic Artificial Muscles (sPAMs) arranged radially around the backbone and extending along the robot's whole length. This design simplifies navigation of the robot by decoupling steering and extension. To navigate to a destination, the robot is steered to point at the destination, and the extension degree-of-freedom is used to reach it. We present models and experimentally verify the sPAMs and growing robot kinematics. The kinematic model has a mean position accuracy of 5.5 cm for predicting the tip position of a 42 cm long robot. Control of the growing robot is demonstrated using an eye-inhand visual servo control law that enables growth of the robot to designated locations.

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Series pneumatic artificial muscles (sPAMs) and application to a soft continuum robot

Cited by 145 publications

References 23 publications

A soft matter computer for soft robots

A soft matter computer for soft robots

Soft Robotics as an Enabling Technology for Agroforestry Practice and Research

A Soft, Steerable Continuum Robot That Grows via Tip Extension

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