scholarly journals Phototunable self-oscillating system driven by a self-winding fiber actuator

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Zhiming Hu ◽  
Yunlong Li ◽  
Jiu-an Lv
Keyword(s):  
Degrees Of Freedom ◽  
Soft Materials ◽  
Constant Stimulus ◽  
Liquid Crystal Polymers ◽  
Intelligent Machines ◽  
Helix Formation ◽  
Oscillating Systems ◽  
Oscillation Modes ◽  
Mechanical Transduction ◽  
Advanced Robotics

AbstractSelf-oscillating systems that enable autonomous, continuous motions driven by an unchanging, constant stimulus would have significant applications in intelligent machines, advanced robotics, and biomedical devices. Despite efforts to gain self-oscillations have been made through artificial systems using responsive soft materials of gels or liquid crystal polymers, these systems are plagued with problems that restrict their practical applicability: few available oscillation modes due to limited degrees of freedom, inability to control the evolution between different modes, and failure under loading. Here we create a phototunable self-oscillating system that possesses a broad range of oscillation modes, controllable evolution between diverse modes, and loading capability. This self-oscillating system is driven by a photoactive self-winding fiber actuator designed and prepared through a twistless strategy inspired by the helix formation of plant-tendrils, which endows the system with high degrees of freedom. It enables not only controllable generation of three basic self-oscillations but also production of diverse complex oscillatory motions. Moreover, it can work continuously over 1270000 cycles without obvious fatigue, exhibiting high robustness. We envision that this system with controllable self-oscillations, loading capability, and mechanical robustness will be useful in autonomous, self-sustained machines and devices with the core feature of photo-mechanical transduction.

Dexterous Hybrid Robotics for High Precision Applications

2018 ◽  
Author(s):  
Nolan Jackson ◽  
Mitchell Crowther ◽  
Minchul Shin
Keyword(s):  
Degrees Of Freedom ◽  
Pressure Range ◽  
Mechanical Design ◽  
Modern Human ◽  
Soft Material ◽  
Robotic Hands ◽  
Advanced Robotics ◽  
Air Compressors ◽  
Pneumatic Pump ◽  
Advanced Applications

Robotic grippers are useful in designing prosthetics and manufacturing. “Robotic hands often fall into two categories: simple and highly specialized grippers often used in manufacturing, and general and highly complicated grippers designed for a variety of tasks.” Ramond et al. [1] Within these two categories there are two main categories of research. These are hard structure and soft structure robotics. Hard structure robotics rely on a mechanical design with a motor or actuator to move a hard-linked part. Soft structure uses a mechanical design, soft material and a pneumatic pump to create the desired movement. The soft material is designed in a way that when it is pumped full of a fluid (i.e. air) it has a specific deformation. Hard robotics have an advantage in their ability to output a large force, but soft robotics have increased degrees of freedom. Dexterity (readiness and grace in physical movement) is another advantage over hard robotics. This project focuses on the process of designing actuators that can feasibly be used for devices falling into either of the two main categories of robotics. Such an actuator could be effectively implemented toward simple applications such as manufacturing-style gripping devices to advanced applications found in modern human prosthetics or areas where high dexterity combined with a delicate touch are required. The simulations show that the designs created work within a pressure range of 0.5 PSI to 1 PSI. This low pressure does not output a lot of force. The high dexterity and small air compressors needed make it a good design for use in areas like manufacturing or medical. If a stronger material was applied to these designs allowing the designs to handle higher pressures these designs could output much higher forces. This increase would make the designs more usable in areas like prosthetics and advanced robotics.

scholarly journals Electronic structure at coarse-grained resolutions from supervised machine learning

2019 ◽  
Vol 5 (3) ◽  
pp. eaav1190 ◽  
Author(s):  
Nicholas E. Jackson ◽  
Alec S. Bowen ◽  
Lucas W. Antony ◽  
Michael A. Webb ◽  
Venkatram Vishwanath ◽  
...  
Keyword(s):  
Machine Learning ◽  
Electronic Structure ◽  
Quantum Chemical Calculations ◽  
Spatial Resolution ◽  
Quantum Chemical ◽  
Degrees Of Freedom ◽  
Soft Materials ◽  
Conformational Space ◽  
Supervised Machine Learning ◽  
Coarse Grained

Computational studies aimed at understanding conformationally dependent electronic structure in soft materials require a combination of classical and quantum-mechanical simulations, for which the sampling of conformational space can be particularly demanding. Coarse-grained (CG) models provide a means of accessing relevant time scales, but CG configurations must be back-mapped into atomistic representations to perform quantum-chemical calculations, which is computationally intensive and inconsistent with the spatial resolution of the CG models. A machine learning approach, denoted as artificial neural network electronic coarse graining (ANN-ECG), is presented here in which the conformationally dependent electronic structure of a molecule is mapped directly to CG pseudo-atom configurations. By averaging over decimated degrees of freedom, ANN-ECG accelerates simulations by eliminating backmapping and repeated quantum-chemical calculations. The approach is accurate, consistent with the CG spatial resolution, and can be used to identify computationally optimal CG resolutions.

scholarly journals Exploiting short-term memory in soft body dynamics as a computational resource

2014 ◽  
Vol 11 (100) ◽  
pp. 20140437 ◽  
Author(s):  
K. Nakajima ◽  
T. Li ◽  
H. Hauser ◽  
R. Pfeifer
Keyword(s):  
Degrees Of Freedom ◽  
Closed Loop ◽  
Short Term Memory ◽  
Soft Materials ◽  
Computational Resource ◽  
Soft Body ◽  
Short Term ◽  
Term Memory ◽  
Loop Control ◽  
Body Dynamics

Soft materials are not only highly deformable, but they also possess rich and diverse body dynamics. Soft body dynamics exhibit a variety of properties, including nonlinearity, elasticity and potentially infinitely many degrees of freedom. Here, we demonstrate that such soft body dynamics can be employed to conduct certain types of computation. Using body dynamics generated from a soft silicone arm, we show that they can be exploited to emulate functions that require memory and to embed robust closed-loop control into the arm. Our results suggest that soft body dynamics have a short-term memory and can serve as a computational resource. This finding paves the way towards exploiting passive body dynamics for control of a large class of underactuated systems.

Advanced robotics & intelligent machines

Mechatronics ◽  
1996 ◽  
Vol 6 (7) ◽  
pp. 853-854
Author(s):  
D. Subbaram Naidu
Keyword(s):  
Intelligent Machines ◽  
Advanced Robotics
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