76 research outputs found

    Angle Control of a Pneumatically Driven Musculoskeletal Model Based on Coordination of Agonist-Antagonist Muscle

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    In recent years, researchers have been actively pursuing research into developing robots that can be useful in many fields of industry (e.g., service, medical, and aging care). Such robots must be safe and flexible so that they can coexist with people. Pneumatic actuators are useful for achieving this goal because they are lightweight units with natural compliance. Our research focuses on joint angle control for a pneumatically driven musculoskeletal model. In such a model, we use a one-degree-of-freedom joint model and a five-fingered robot hand as test beds. These models are driven by low pressure-driven pneumatic actuators, and mimic the mechanism of the human hand and musculoskeletal structure, which has an antagonistic muscle pair for each joint. We demonstrated a biologically inspired control method using the parameters antagonistic muscle ratio and antagonistic muscle activity. The concept of the method is based on coordination of an antagonistic muscle pair using these parameters. We have investigated the validity of the proposed method both theoretically and experimentally, developed a feedback control system, and conducted joint angle control by implementing the test beds.ArticleJournal of Mechanics Engineering and Automation. 2(12):709-719 (2012)journal articl

    System Design of a Cheetah Robot Toward Ultra-high Speed

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    High-speed legged locomotion pushes the limits of the most challenging problems of design and development of the mechanism, also the control and the perception method. The cheetah is an existence proof of concept of what we imitate for high-speed running, and provides us lots of inspiration on design. In this paper, a new model of a cheetah-like robot is developed using anatomical analysis and design. Inspired by a biological neural mechanism, we propose a novel control method for controlling the muscles' flexion and extension, and simulations demonstrate good biological properties and leg's trajectory. Next, a cheetah robot prototype is designed and assembled with pneumatic muscles, a musculoskeletal structure, an antagonistic muscle arrangement and a J-type cushioning foot. Finally, experiments of the robot legs swing and kick ground tests demonstrate its natural manner and validate the design of the robot. In the future, we will test the bounding behaviour of a real legged system

    Adaptive backstepping position control of pneumatic anthropomorphic robotic hand

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    This paper presents a nonlinear adaptive backstepping algorithm for position control of an anthropomorphic robotic hand. The contraction force of PAM actuator has been modeled based on an empirical approach and the overall finger is represented as a nonlinear second order system, taking into account the system uncertainty caused by hysteresis phenomenon in PAM actuators. Adaptive backstepping controller has been developed by formulating the estimator of the system uncertainty. To improve the performance of controller, a cascade control system is developed by combining a conventional PID control, as an inner loop controller, with the adaptive back stepping position control as the outer loop of the controller. Finally, a simulation test is conducted to evaluate the performance of the proposed controller

    Biomimetic leg design and passive dynamics of Dolomedes aquaticus

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    Spiders provide working models for agile, efficient miniature passive-dynamic robots. Joints are extended by haemoplymph (hydraulic) pressure and flexed by muscle-tendon systems. Muscle contraction in the prosoma leads to an increase in hydraulic pressure and subsequently leg extension. Analysis of body kinematics the New Zealand fishing spider, Dolomedes aquaticus indicates that elastic plates around the joints absorb energy from the ground reaction force when the force vector points backwards (i.e. would decelerate the spider’s body in the direction of locomotion) and release it to provide forward thrust as the leg swings backwards. In addition to improving energy efficiency, this mechanism improves stability by passively absorbing energy from unpredictable foot-ground impacts during locomotion on uneven terrain. These principles guided an iterative design methodology using a combination of 3D modelling software and 3D printing techniques. I compared and contrasted compliant joints made of a variety of plastic materials. The final 3D-printed spider leg prototype has a stiff ABS exoskeleton joined by a compliant polypropylene backbone. The entire structure envelopes a soft silicone pneumatic bladder. FEA analysis was used to determine the ideal shape and behavior of the pneumatic bladder to actuate the exoskeleton. The spider leg can be flexed and contracted depending on the input pressure. To laterally actuate this pneumatic spider leg I designed and developed a fabrication system that uses vacuum injection molding to produce an integrated mesh sleeve/elastomer pneumatic actuator. I designed an apparatus to measure pressure and contraction of silicone and latex pneumatic muscles when inflated. I analyzed the non-linear pressure-contraction relationships of silicone versus latex pneumatic muscles, and also derived force-contraction relationships. From efficiency studies, both media muscles proved to be inefficient and the measuring apparatus needs to be more robust to prevent leaking air. The fabrication process still offers the possibility of a quick and efficient method of creating pneumatic muscles. A spider-like robot that implements these pneumatic muscles and pneumatic leg design could be used to explore the efficiency and stability of passive dynamic legged locomotion in spider-like robots

    Stability and Performance Improvement in Haptic Human-Robot Interaction

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    The goal of this research is to develop theories, methods, and tools to understand the mechanisms of neuromotor adaptation in human-robot physical interaction, in order to improve the stability and performance of the interaction. Human power-assisting systems (e.g., powered lifting devices that aid human operators in manipulating heavy or bulky loads) require physical contact between the operator and machine, creating a coupled dynamic system. This dynamic coupling has been shown to introduce inherent instabilities and performance degradation due to a change in human stiffness; when instability is encountered, a human operator often attempts to control the oscillation by stiffening their arm, which leads to a stiffer system with more instability. Robot co-worker controllers must account for this issue. In this work we set out to 1) understand the association between neuromuscular adaptations and system performance limits, 2) develop probabilistic methods to classify and predict the transition of operator’s cognitive and physical states from physiological measures, and 3) integrate this knowledge into a structure of shared human-robot control. We developed a model of the human operator endpoint stiffness, characterized at the musculoskeletal level, that can account for deliberate stiffness increase at the endpoint through the incorporation of muscle coactivation. We also developed a switching admittance control approach which can account for changes in the operator’s muscle coactivation and is able to generate cognitive states in an unsupervised manner, given a relevant training dataset. Finally, a novel variable admittance control approach, which significantly reduces grasp contact instability commonly encountered in fixed admittance control settings, was developed, analytically derived, and provides solutions for both constant mass and variable mass parameter cases.Ph.D
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