Embodied Intelligence &amp; Morphological Computation in Soft Robotics Community: Collaborations, Coordination, and Perspective

Sadati, S. M. Hadi; ElDiwiny, Marwa; Nurzaman, Surya G.; Iida, Fumiya; Nanayakkara, Thrishantha

doi:10.1088/1757-899x/1261/1/012005

Cited by 5 publications

(1 citation statement)

References 13 publications

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“…Another field with a long history of contributing to applied co‐design methodology is embodied intelligence and artificial life. [ 175–177 ] Rather than use neuroscience‐inspired methods like neural networks, the artificial life community has favored machine learning techniques inspired by biological evolution and heredity, making use of evolutionary algorithms as well as differentiable simulations to tackle co‐design problems. Much like our own proposal, the artificial life community seeks to design autonomous agents whose material and cognitive make‐up are well‐adapted to their environmental niche.…”

Section: Navigating the Design Spaces Of Soft Roboticsmentioning

confidence: 99%

Materializing Autonomy in Soft Robots across Scales

Berrueta,

Murphey,

Truby

2023

Advanced Intelligent Systems

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The impressive capabilities of living organisms arise from the way autonomy is materialized by their bodies. Across scales, living beings couple computational or cognitive intelligence with physical intelligence through body morphology, material multifunctionality, and mechanical compliance. While soft robotics has advanced the design and fabrication of physically intelligent bodies, the integration of information‐processing capabilities for computational intelligence remains a challenge. Consequently, perception and control limitations have constrained how soft robots are built today. Progress toward untethered autonomy will require deliberate convergence in how the field codevelops new materials, fabrication methods, and control strategies for soft robots. Here, a new perspective is put forward: that researchers should use tasks alone to impose material and information constraints on soft robot design. A conceptual framework is proposed for a task‐first design paradigm that sidesteps limitations imposed by control strategies. This framework allows emergent synergies between material and information processing properties of soft matter to be readily exploited for task‐capable agents. Particular attention is paid to the scale dependence of solutions. Finally, an outlook is presented on emerging research opportunities for achieving autonomy in future soft robots as large as elephant trunks and as small as paramecia.

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Section: Navigating the Design Spaces Of Soft Roboticsmentioning

confidence: 99%

Materializing Autonomy in Soft Robots across Scales

Berrueta,

Murphey,

Truby

2023

Advanced Intelligent Systems

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Perspectives on Intelligence in Soft Robotics

Kortman,

Mazzolai,

Sakes

et al. 2024

Advanced Intelligent Systems

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Engineers frequently aim to streamline environmental factors to facilitate the effective operation of robots. However, in nature, environmental considerations play a crucial role in shaping the embodiment of organisms. To comply robots with the complexity of real‐world environments, embedding similar intelligence is key. In the field of soft robotics, various approaches offer insight into how intelligence can be integrated into artificial agents. A discussed topic is the intricate relationship between the brain and the body at the core of intelligence in robots. The goal of this article is, therefore, to unravel the strategies to implement different types of intelligence currently adopted in soft robots. A classification is made by making a distinction between agents that adapt to their environment by 1) their adaptive shape, 2) their adaptive functionality, and 3) their adaptive mechanics. Additionally, the perspectives on intelligence based on their computational approach are distinguished: centralized computation, decentralized computation, or embedded computation. It is concluded that a tailored robotic design approach attuned to specific environmental demands is needed. To unlock the full potential of soft robots, a fresh perspective on embodied intelligence is described, so‐called mechanical intelligence, emphasizing the robot's responsiveness to changing external conditions of a real‐world environment.

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Intelligence as Computation

Brock

2024

IOP Conf. Ser.: Mater. Sci. Eng.

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This paper proposes a specific conceptualization of intelligence as computation. This conceptualization is intended to provide a unified view for all disciplines of intelligence research. Already, it unifies several conceptualizations currently under investigation, including physical, neural, embodied, morphological, and mechanical intelligences. To achieve this, the proposed conceptualization explains the differences among existing views by different computational paradigms, such as digital, analog, mechanical, or morphological computation. Viewing intelligence as a composition of computations from different paradigms, the challenges posed by previous conceptualizations are resolved. Intelligence is hypothesized as a multi-paradigmatic computation relying on specific computational principles. These principles distinguish intelligence from other, non-intelligent computations. The proposed conceptualization implies a multi-disciplinary research agenda that is intended to lead to unified science of intelligence.

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Embodied Intelligence & Morphological Computation in Soft Robotics Community: Collaborations, Coordination, and Perspective

Cited by 5 publications

References 13 publications

Materializing Autonomy in Soft Robots across Scales

Materializing Autonomy in Soft Robots across Scales

Perspectives on Intelligence in Soft Robotics

Intelligence as Computation

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