Development of constant torque device and its application to power assist systems

Minamiyama, Yasuhiro; Kiyota, Takanori; Mori, Takahiro; Sugimoto, Noboru

doi:10.1109/aim.2014.6878077

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…In the case of Mobility Support, i.e., where the power assistance is continuous, the main motivation to use a CTM is to reduce the torque-requirements of the task that needs to be performed [20][21][22][23]. Another motivation for the use of CTMs is a principle that will be named 'Zero Torque Shift' in this paper.…”

Section: Functional Classificationmentioning

confidence: 99%

Constant Torque Mechanisms: A Survey

Saerens

Furnémont

Legrand

et al. 2022

Applied Mechanics Reviews

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In this paper an overview is given of all types of constant torque mechanisms (CTMs) based on both function and structure. Based on their architecture they can be divided into five distinct categories which all have their specific behaviour. It is also shown that these CTMs can be divided into two application types, namely power assistance or torque stabilization. Due to the fact that in research mainly constant force mechanisms (CFMs) have been tackled, also some explanation is given on how CFMs can be transformed into CTMs. It is also shown that some of these CTMs have a very high specific energy which can make that they have potential application as energy storage/power provider in novel fields like robotics where they have almost not been used yet.

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Section: Functional Classificationmentioning

confidence: 99%

Constant Torque Mechanisms: A Survey

Saerens

Furnémont

Legrand

et al. 2022

Applied Mechanics Reviews

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“…This approach can be comparable to the constant force approach for power assist manipulation. 38 In equation (9), W h and W a are other weighing factors. We estimate a r ≈ 1.0 m/s 2 , W e = 1 , W h = 0.5 , W a = 0.5 , and f h x r ≈ 4.0 N (it is much larger than simulated weight, 2.45 N 14 ) empirically being motivated by the kinematics and kinetics data in Figure 7 and Table 4.…”

Section: Cognition-based Intelligent Control Strategiesmentioning

confidence: 99%

Calibrating intuitive and natural human–robot interaction and performance for power-assisted heavy object manipulation using cognition-based intelligent admittance control schemes

Rahman

Ikeura

2018

International Journal of Advanced Robotic Systems

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In the first step, a one degree of freedom power assist robotic system is developed for lifting lightweight objects. Dynamics for human-robot co-manipulation is derived that includes human cognition, for example, weight perception. A novel admittance control scheme is derived using the weight perception-based dynamics. Human subjects lift a small-sized, lightweight object with the power assist robotic system. Human-robot interaction and system characteristics are analyzed. A comprehensive scheme is developed to evaluate the human-robot interaction and performance, and a constrained optimization algorithm is developed to determine the optimum human-robot interaction and performance. The results show that the inclusion of weight perception in the control helps achieve optimum human-robot interaction and performance for a set of hard constraints. In the second step, the same optimization algorithm and control scheme are used for lifting a heavy object with a multidegree of freedom power assist robotic system. The results show that the human-robot interaction and performance for lifting the heavy object are not as good as that for lifting the lightweight object. Then, weight perception-based intelligent controls in the forms of model predictive control and vision-based variable admittance control are applied for lifting the heavy object. The results show that the intelligent controls enhance human-robot interaction and performance, help achieve optimum human-robot interaction and performance for a set of soft constraints, and produce similar human-robot interaction and performance as obtained for lifting the lightweight object. The human-robot interaction and performance for lifting the heavy object with power assist are treated as intuitive and natural because these are calibrated with those for lifting the lightweight object. The results also show that the variable admittance control outperforms the model predictive control. We also propose a method to adjust the variable admittance control for three degrees of freedom translational manipulation of heavy objects based on human intent recognition. The results are useful for developing controls of human friendly, high performance power assist robotic systems for heavy object manipulation in industries.

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