Dual-mode variable stiffness actuator using two-stage worm gear transmission for safe robotic manipulators

Jeong, Hyunhwan; Cheong, Joono; Kwon, SangJoo

doi:10.1007/s12541-015-0231-x

Cited by 5 publications

(3 citation statements)

References 11 publications

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“…The second actuator adjusts the stiffness by changing the transmission-ratio or transmission-angle, controlling the pre-stress on a nonlinear spring or the physical stiffness properties [19,20]; as advantage, the output torque is not influenced. Jeong et al [21] reported on the use of two-worm gear transmission to compress two coiled springs and change their output stiffness. In continuum robotics with wire transmission, increasing tension in the wires is used to increase stiffness [11,22].…”

Section: Variable Stiffness and Impedance Actuatorsmentioning

confidence: 99%

Low power consumption mini rotary actuator with SMA wires

Manfredi

Huan

Cuschieri

2017

Smart Mater. Struct.

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Shape memory alloys (SMAs) are smart materials widely used as actuators for their high power to weight ratio despite their well-known low energy efficiency and limited mechanical bandwidth. For robotic applications, SMAs exhibit limitations due to high power consumption and limited stroke, varying from 4% to 7% of the total length. Hysteresis, during the contraction and extension cycle, requires a complex control algorithm. On the positive side, the small size and low weight are eminently suited for the design of mini actuators for robotic platforms. This paper describes the design and construction of a light weight and low power consuming mini rotary actuator with on-board contact-less position and force sensors. The design is specifically intended to reduce (i) energy consumption, (ii) dimensions of the sensory system, and (iii) provide a simple control without any need for SMA characterisation. The torque produced is controlled by on-board force sensors. Experiments were performed to investigate the energy consumption and performance (step and sinusoidal angle profiles with a frequency varying from 0.5 to 10 Hz and maximal amplitude of ). We describe a transient capacitor effect related to the SMA wires during the sinusoidal profile when the active SMA wire is powered and the antagonist one switched-off, resulting in a transient current time varying from 300 to 400 ms.

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Section: Variable Stiffness and Impedance Actuatorsmentioning

confidence: 99%

Low power consumption mini rotary actuator with SMA wires

Manfredi

Huan

Cuschieri

2017

Smart Mater. Struct.

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“…9 Another potential benefit of a worm-wheel gear is its unique property of self-locking or non-backdrivability that allows it to be driven on the side of input and not back driven on the load side. [10][11][12][13][14] Therefore, actuators do not need to stay powered all the time to hold or lift the loads in a particular position. These promising features make the worm-wheel gear transmission a desirable candidate for several robotic applications, including rescue operations.…”

Section: Introductionmentioning

confidence: 99%

Control of a worm-wheel gear driven rescue robot with friction compensation and its experimental verification

Shoaib,

Kim,

Park

et al. 2023

Advances in Mechanical Engineering

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This paper presents the control of a rescue robot driven by the worm-wheel gear transmission. In the modeling process, the load-dependent friction of the worm-wheel gear is considered, and the governing equations for static and dynamic analyses are formulated. Especially we examine the dependency of break-in joint torques on the loading torque and directionality of motion. The friction parameters of the worm-wheel gear of a physical rescue robot are identified through experimental investigation. A friction compensation controller is then designed based on the modeling results and experimental operating conditions. And the designed controller is applied to a dual-arm rescue robot to validate its effectiveness.

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“…That makes robots safe and improves their adaptability in the human-robot cooperation field [1]. In literature, many applications of the variable stiffness system (VSS) [2] such as shock absorbance [3][4][5], stiffness variability with a constant load [6,7], and cyclic movement [8], the safety robot [9] proved the effectiveness of the variable stiffness system although this research focused on tuning the system stiffness optimally. Normally, primary torque or force of these VSSs is generated by electric motors [3][4][5]8,9], or pneumatic actuators [6,7,9].…”

Section: Introductionmentioning

confidence: 99%

RBF Neural Network Based Backstepping Control for an Electrohydraulic Elastic Manipulator

2019

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An electrohydraulic elastic manipulator (EEM) is a kind of variable stiffness system (VSS). The equilibrium position and stiffness controller are the two main problems which must be considered in the VSS. When the system stiffness is changed for a specific application, the system dynamics are significantly altered, which is a challenge in controlling equilibrium position. This paper presents adaptive robust control for controlling the equilibrium position of the EEM under the presence of the variable stiffness. The proposed control includes sliding mode controls (SMCs), radial basis function neural network (RBFNN), and backstepping technique. The RBFNN is employed to compensate for the uncertainties and the variant stiffness in mechanical dynamics and hydraulic dynamics. The Lyapunov approach and projection algorithm are used to derive the adaptive laws of the RBFNN and to prove the stability and robustness of the entire EEM. Finally, some experiments are implemented and compared with other controllers to prove the effectiveness of the proposed method with the variant stiffness.

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Dual-mode variable stiffness actuator using two-stage worm gear transmission for safe robotic manipulators

Cited by 5 publications

References 11 publications

Low power consumption mini rotary actuator with SMA wires

Low power consumption mini rotary actuator with SMA wires

Control of a worm-wheel gear driven rescue robot with friction compensation and its experimental verification

RBF Neural Network Based Backstepping Control for an Electrohydraulic Elastic Manipulator

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