1388 39 17914 2 66492 document 17914 multimodal_data.zip application/zip 3bd3474bdfb5b25c4d42668d4f44bcaa MD5 679834 2024-04-11 21:28:57 https://researchdata.bath.ac.uk/1388/1/multimodal_data.zip 1388 1 1 application/zip other en public cc_by

multimodal_data.zip

data archive 10752 disk0/00/00/13/88 2024-05-07 14:07:55 2024-07-15 11:00:15 2024-05-07 14:07:55 data_collection show Al Gorkem Anil G.Al@bath.ac.uk 0000-0003-4098-6065 University of Bath TRUE EA0090 dept_elec_eng machine learning, human-robot interaction, multimodal sensing module, robotics, sensing data The dataset is divided into 2 main folders containing hand gesture and touch data. Gesture_Data folder contains data collected by performing four hand gestures; up, down, left, and right. There's also error data on mistakes made during these gestures. Touch_Data folder contains IMU data collected from the tactile sensor applying force on four different contact locations and from the idle case where no contact was made with the tactile sensor. The aim of this data collection is to present that the proposed sensing module can establish reliable multimodal communication channels between humans and industrial robots, thereby enhancing the interaction efficiency and user experience in automated environments. 2024-04-22 University of Bath public RightsHolder University of Bath Engineering and Physical Sciences Research Council https://doi.org/10.13039/501100000266 EP/V051083/1 Manufacturing in Hospital: BioMed 4.0 cent_aur cent_dmade The methodology can be found in the associated paper. en 1 10.15125/BATH-01388 https://doi.org/10.1109/LSENS.2024.3391876 pub open Dataset