Enhancing Robotic Perception and Adaptability through Sensor Fusion and Origami-Inspired Designs
Enhancing Robotic Perception and Adaptability through Sensor Fusion and Origami-Inspired Designs
This research introduces a compact mobile robot that uses origami-inspired wheels for locomotion and active sensing geometry control. The robot's changing chassis pitch sweeps a 2D LiDAR through intermediate elevations, while an IMU and fusion node project LiDAR data into RGB-D depth streams. The system improves depth coverage and reduces invalid depth fractions in both indoor and outdoor environments.
Source: arXiv Robotics — research abstracts · Read original article ↗
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Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
Reported numbers
payload
300
weight
2
cost
300
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arXiv:2610.09828v1 Announce Type: new Abstract: Compact mobile robots must recover scene geometry under changing lighting and surface texture while working within tight payload and cost limits. We present a compact mobile robot that uses origami-inspired wheels for locomotion and active control of its sensing geometry. As the wheels move between terrain-adaptive configurations, the changing chassis pitch sweeps a 2D
Open source S2
outdoor sunlit area, with three runs per sensor configuration in each setting. Mean full-frame invalid-depth fractions fell from 21% to 11% indoors and from 48% to 18% outdoors. The prototype combines improved depth coverage with a continuously adjustable LiDAR viewpoint using the same actuation that reconfigures its wheels.
Open source S4
LiDAR through intermediate elevations; held wheel positions provide a chosen viewing angle. An IMU accounts for chassis attitude, and a fusion node projects LiDAR returns into the RGB-D depth stream supplied to RTAB-Map. The arrangement uses the wheel actuation already present on a sub-300 USD, sub-2 kg prototype to extend the scanner's viewing geometry. We assess depth fusion in a textureless indoor corridor and an
Open source S3
Source：arXiv Robotics — research abstracts · arxiv.org