Studies of motor synergies in generating optimal goal-directed movements in human-like robotic arm

Fu, Kin Chung Denny; Nakamura, Yutaka; Yamamoto, Tomoko; Ishiguro, Hiroshi

doi:10.1109/robio.2012.6491067

Cited by 3 publications

(4 citation statements)

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“…Dynamic models that simulate the capabilities of the human arm have also been used to generate biologically-inspired arm motion [35,36]. For example, Fu et al [35] investigated how the motor synergies hypothesis behind the motion of human arms can improve planning reaching movements for a planar manipulator. Specifically, motor synergies are responsible for the activation of a group of muscles in a coordinated manner.…”

Section: General Insights On Approaching Human-likeness Of Arm Motionmentioning

confidence: 99%

“…The general planning strategy is formulated with a framework for optimal control that minimizes the contribution of the control activation inputs acting on the joints of the manipulator. Fu et al [35] proposed the extraction of motor synergies from control inputs to solve the optimization problem in a lower dimensionality and, consequently, decrease the computational burden of the algorithm. Experiments on a 3-DOFs planar human-like arm moving on a bi-dimensional workspace demonstrated how the reduction of dimensionality generally improved the performance of planning by providing a higher success rate and a lower cost of the objective function spending less computation time.…”

Section: General Insights On Approaching Human-likeness Of Arm Motionmentioning

confidence: 99%

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Human-Like Arm Motion Generation: A Review

2020

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In the last decade, the objectives outlined by the needs of personal robotics have led to the rise of new biologically-inspired techniques for arm motion planning. This paper presents a literature review of the most recent research on the generation of human-like arm movements in humanoid and manipulation robotic systems. Search methods and inclusion criteria are described. The studies are analyzed taking into consideration the sources of publication, the experimental settings, the type of movements, the technical approach, and the human motor principles that have been used to inspire and assess human-likeness. Results show that there is a strong focus on the generation of single-arm reaching movements and biomimetic-based methods. However, there has been poor attention to manipulation, obstacle-avoidance mechanisms, and dual-arm motion generation. For these reasons, human-like arm motion generation may not fully respect human behavioral and neurological key features and may result restricted to specific tasks of human-robot interaction. Limitations and challenges are discussed to provide meaningful directions for future investigations.

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Section: General Insights On Approaching Human-likeness Of Arm Motionmentioning

confidence: 99%

Section: General Insights On Approaching Human-likeness Of Arm Motionmentioning

confidence: 99%

Human-Like Arm Motion Generation: A Review

2020

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“…H (θ θ θ) θ θ θ + V θ θ θ, θ θ θ θ θ θ + G (θ θ θ) = τ (θ θ θ, u u u p ) ( 8 ) where θ θ θ = [θ1 θ2 θ3] T and u u u p = [u1 . .…”

Section: Appendix: Human-like Arm Modelunclassified

“…3) How should motor synergies be utilized better? Note that [8] includes some previous results for the first and second problems.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Motor Synergies Utilization for Optimal Movement Generation for a Human-like Robotic Arm

Nakamura

Yamamoto

et al. 2013

Int. J. Autom. Comput.

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Controlling human-like robots with musculoskeletal structure has been a challenging problem in engineering. In biological studies, motor synergy hypothesis has been proposed as a solution in order to control high degree-of-freedom and complex human body. In this paper, we focus on exploring the applicability of motor synergies in generating goal-directed movements by optimal control in a human-like robotic arm. We focus on three problems: 1) Can motor synergies facilitate the solving of optimal control problem? 2) What properties should motor synergies have in order to achieve tasks? 3) How should motor synergies be utilized better? For the first problem we show that goal-directed movements can be achieved by utilizing motor synergies which have properties of achieving the goals. For the second problem, we testify motor synergies which have different properties and discover that energy efficiency is an important aspect in motor synergies which can also be utilized to achieve goal-directed movements. This discovery also implies that we can obtain motor synergies by other ways rather than from goal-directed optimal control signals. For the third problem, we show that the control complexity can be further reduced by utilizing a subset of motor synergies which are effective to achieve goals.

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