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http://dx.doi.org/10.3389/frobt.2022.1050658 | DOI Listing |
Front Neurol
January 2025
Department of Rehabilitation Medicine, Hirosaki University Graduate School of Medicine, Hirosaki, Japan.
Sensors (Basel)
January 2025
Future Robotics Organization, Waseda University, Tokyo 169-8050, Japan.
Wearable sensor technologies are rapidly evolving and expanding their reach into critical wellness and healthcare applications [...
View Article and Find Full Text PDFBrain Sci
January 2025
Behavioral and Robotic Neurorehab Unit, IRCCS Centro Neurolesi "Bonino Pulejo", 98123 Messina, Italy.
It was a great pleasure to be the guest editor for the Special Issue on understanding the use of rehabilitation devices in neurological diseases [...
View Article and Find Full Text PDFFront Plant Sci
January 2025
Institute of Agricultural Facilities and Equipment, Jiangsu Academy of Agricultural Sciences, Nanjing, Jiangsu, China.
Three-dimensional (3D) LiDAR is crucial for the autonomous navigation of orchard mobile robots, offering comprehensive and accurate environmental perception. However, the increased richness of information provided by 3D LiDAR also leads to a higher computational burden for point cloud data processing, posing challenges to real-time navigation. To address these issues, this paper proposes a 3D point cloud optimization method based on the octree data structure for autonomous navigation of orchard mobile robots.
View Article and Find Full Text PDFFront Robot AI
January 2025
Neuro-robotics Laboratory, Department of Robotics, Graduate School of Engineering, Tohoku University, Sendai, Japan.
Reliable proprioception and feedback from soft sensors are crucial for enabling soft robots to function intelligently in real-world environments. Nevertheless, soft sensors are fragile and are susceptible to various damage sources in such environments. Some researchers have utilized redundant configuration, where healthy sensors compensate instantaneously for lost ones to maintain proprioception accuracy.
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