Modeling and Analysis of a High-Displacement Pneumatic Artificial Muscle With Integrated Sensing

We present a high-displacement pneumatic artificial muscle made of textiles or plastics that can include integrated electronics to sense its pressure and displacement. Compared to traditional pneumatic muscle actuators such as the McKibben actuator and other more recent soft actuators, the actuator described in this paper can produce a much higher (40~65%) contraction ratio. In this paper, we describe the design, fabrication, and evaluation of the actuator, as well as the manufacturing process used to create it. We demonstrate the actuator design with several examples that produce 120 and 300 N at pressures of 35 and 105 kPa, respectively, and have contraction ratios of 40–65%

Scaling hard vertical surfaces with compliant microspine arrays

A new approach for climbing hard vertical surfaces has been developed that allows a robot to scale concrete, stucco, brick and masonry walls without using suction or adhesives. The approach is inspired by the mechanisms observed in some climbing insects and spiders and involves arrays of microspines that catch on surface asperities. The arrays are located on the toes of the robot and consist of a tuned, multi-link compliant suspension. In this paper we discuss the fundamental issues of spine allometric scaling versus surface roughness and the suspension needed to maximize the probability that each spine will find a useable surface irregularity and to distribute climbing tensile and shear loads among many spines. The principles are demonstrated with a new climbing robot that can scale a wide range of exterior walls

Analysis of frequency-smearing models simulating hearing loss

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.Includes bibliographical references (leaves 189-191).by Alan T. Asbeck.M.Eng

Motion Inference Using Sparse Inertial Sensors, Self-Supervised Learning, and a New Dataset of Unscripted Human Motion

In recent years, wearable sensors have become common, with possible applications in biomechanical monitoring, sports and fitness training, rehabilitation, assistive devices, or human-computer interaction. Our goal was to achieve accurate kinematics estimates using a small number of sensors. To accomplish this, we introduced a new dataset (the Virginia Tech Natural Motion Dataset) of full-body human motion capture using XSens MVN Link that contains more than 40 h of unscripted daily life motion in the open world. Using this dataset, we conducted self-supervised machine learning to do kinematics inference: we predicted the complete kinematics of the upper body or full body using a reduced set of sensors (3 or 4 for the upper body, 5 or 6 for the full body). We used several sequence-to-sequence (Seq2Seq) and Transformer models for motion inference. We compared the results using four different machine learning models and four different configurations of sensor placements. Our models produced mean angular errors of 10–15 degrees for both the upper body and full body, as well as worst-case errors of less than 30 degrees. The dataset and our machine learning code are freely available

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A new approach for climbing hard vertical surfaces has been developed that allows a robot to scale concrete, stucco, brick and masonry walls without using suction or adhesives. The approach is inspired by the mechanisms observed in some climbing insects and spiders and involves arrays of microspines that catch on surface asperities. The arrays are located on the toes of the robot and consist of a tuned, multi-link compliant suspension. The fundamental issues of spine allometric scaling versus surface roughness are discussed and the interaction between spines and surfaces is modeled. The toe suspension properties needed to maximize the probability that each spine will find a useable surface irregularity and to distribute climbing loads among many spines are detailed. The principles are demonstrated with a new climbing robot, SpinybotII, that can scale a wide range of flat exterior walls, carry a payload equal to its own weight

microspine

hard vertical surfaces with complian

SpinybotII: Climbing Hard Walls With Compliant Microspines

Abstract--A new climbing robot has been developed that can scale flat, hard vertical surfaces including concrete, brick, stucco and masonry without using suction or adhesives. The robot can carry a payload equal to its own weight and can cling without consuming power. It employs arrays of miniature spines that catch opportunistically on surface asperities. The approach is inspired by the mechanisms observed in some climbing insects and spiders. This paper covers the analysis and implementation of the approach, focusing on issues of spine/surface interaction and compliant suspension design. I Index Terms—Robotics, Mechanisms