Computer vision can be used by robotic leg prostheses and exoskeletons to improve high-level transitions between different locomotion modes (e.g., level-ground walking to stair ascent) through the prediction of future environmental states. Here we developed the StairNet dataset to support research and development in vision-based automated stair recognition.

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This dataset consists of a bill of materials (.PDF) for the equipment and materials used in the fabrication of the M-BLUE hardware, and SolidWorks CAD models (.SLDPRT, .SLDASM) of the custom sheet metal components and 3D-printed spacer used in the M-BLUE assembly.

Supplementary material for the article:

C. Nesler, G. Thomas, N. Divekar, E. Rouse, and R. Gregg, "Enhancing Voluntary Motion with Modular, Backdrivable, Powered Hip and Knee Orthoses," IEEE Robotics & Automation Letters, 2022.

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182 Views

This dataset consists of a bill of materials (.PDF) for the equipment and materials used in the fabrication of the M-BLUE hardware, and SolidWorks CAD models (.SLDPRT, .SLDASM) of the custom sheet metal components and 3D-printed spacer used in the M-BLUE assembly.

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35 Views

Any work using this dataset should cite the following paper:

 Nirmalya Thakur, "An open access dataset of tweets related to exoskeletons and 100 research questions, " arXiv [cs.CY], 2022, DOI: 

Instructions: 

Please refer to the paper

Please refer to the above-mentioned paper.

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751 Views

Abstract: Recent advances in computer vision and deep learning are allowing researchers to develop automated environment recognition systems for robotic leg prostheses and exoskeletons. However, small-scale and private training datasets have impeded the widespread development and dissemination of image classification algorithms (e.g., convolutional neural networks) for recognizing the human walking environment.

Instructions: 

*Details on the ExoNet database are provided in the references above. Please email Brokoslaw Laschowski (blaschow@uwaterloo.ca) for any additional questions and/or technical assistance. 

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3855 Views

Previous studies of robotic leg prostheses and exoskeletons with regenerative actuators have focused almost exclusively on level-ground walking applications. Here we analyzed the lower-limb joint mechanical work and power during stand-to-sit movements using inverse dynamics to estimate the biomechanical energy theoretically available for electrical energy regeneration and storage. Nine subjects performed 20 sitting and standing movements while lower-limb kinematics and ground reaction forces were experimentally measured.

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1087 Views