On neuromechanical approaches for the study of biological and robotic grasp and manipulation

Journal of NeuroEngineering and Rehabilitation, Oct 2017

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank and open-minded assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas at the interface of neuromechanics, neuroscience, rehabilitation and robotics.

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On neuromechanical approaches for the study of biological and robotic grasp and manipulation

Valero-Cuevas and Santello Journal of NeuroEngineering and Rehabilitation On neuromechanical approaches for the study of biological and robotic grasp and manipulation Francisco J. Valero-Cuevas 0 1 Marco Santello 2 0 Division of Biokinesiology & Physical Therapy, University of Southern California , Los Angeles, CA , USA 1 Biomedical Engineering Department, University of Southern California , Los Angeles, CA , USA 2 School of Biological and Health Systems Engineering Arizona State University , Tempe, AZ , USA Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank and open-minded assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas at the interface of neuromechanics, neuroscience, rehabilitation and robotics. Neuromuscular control; Hand; Prosthetics Introduction Grasp and manipulation have captivated the imagination and interest of thinkers of all stripes over the millennia; and with enough reverence to even attribute the intellectual evolution of humans to the capabilities of the hand [ 1–3 ]. Simply put, manipulation function is one of the key elements of our identity as a species (for an overview, see [ 4 ]). This is a natural response to the fact that much of our physical and cognitive ability and well-being is intimately tied to the use of our hands. Importantly, we have shaped our tools and environment to match its capabilities (straightforward examples include lever handles, frets in string instruments, and touch-screens). This co-evolution between hand-and-world reinforces the notion that our hands are truly amazing and robust manipulators, as well as rich sensory, perceptual and even social information. It then comes as no surprise that engineers and physicians have long sought to replicate and restore this functionality in machines—both as appendages to robots and prostheses attached to humans with missing upper limbs [ 5 ]. Robotic hands and prostheses have a long and illustrious history, with records of sophisticated articulated hands as early as Gottfried ‘Götz’ von Berlichingen’s iron hand in 1504 [ 6 ]. Other efforts [ 7–11 ] were often fueled by the injuries of war [ 12–15 ] and the Industrial Revolution [16]. The higher survival rate in soldiers who lose upper limbs [ 17, 18 ] and the continual emergence of artificial intelligence [ 19, 20 ] are but the latest impetus. Thus, the past 20 years have seen an explosion in designs, fueled by large scale governmental funding (e.g., DARPA’s Revolutionizing Prosthetics and HAPTIX projects, EU’s INPUT and SOFTPRO projects) and private efforts such as DeepMind. A new player in this space is the potentially revolutionary social network of highquality amateur scientists as exemplified by the FABLAB movement [ 21 ]. They are enabled by ubiquitously accessible and inexpensive 3D printing and additive manufacturing tools [ 22 ], collaborative design databases (www. eng.yale.edu/grablab/openhand/ and others), and communities with formal journals (www.liebertpub.com/ overview/3d-printing-and-additive-manufacturing/621/ and www.journals.elsevier.com/additive-manufacturing/). Grassroots communities have also emerged that can, for example, compare and contrast the (...truncated)


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Francisco J. Valero-Cuevas, Marco Santello. On neuromechanical approaches for the study of biological and robotic grasp and manipulation, Journal of NeuroEngineering and Rehabilitation, 2017, pp. 101,