Robot NAO Learns to Plug Itself In With a Low-Cost Autonomous Charging Dock
Robot NAO Learns to Plug Itself In With a Low-Cost Autonomous Charging Dock
A new open-access study presents an autonomous charging system for the NAO humanoid robot, allowing it to detect low battery, navigate to a wall-mounted docking station, align itself, and resume tasks without human assistance. The system combines hardware elements like conductive pads, a compliant docking station, and an IoT-based control system. Experimental validation in a healthcare setting showed successful autonomous charging across multiple robots, with the authors noting limitations such as lighting sensitivity and suggesting future improvements.
Source: Robotics — Robot learning news discovery · Read original article ↗
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What the source reports
Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.
- Environment
- Controlled physical settingOpen source S15
- Control
- Reported autonomousOpen source S1
Reported numbers
charging time
3–4 hours
View original evidence
The humanoid robot NAO, a familiar face in hospitals, classrooms and assisted-living facilities, has long been undermined by a mundane problem: its battery. Depending on how hard it works, the robot runs for roughly 90 to 120 minutes before needing a recharge that takes three to four hours through its standard interface, forcing caregivers to interrupt sessions and plug it in by hand. A new open-access study publishe
Open source S2distance error
0.61
View original evidence
n took place at the ENEA Research Centre in Casaccia, inside the Technologies for Quality of Life Laboratory, in an indoor setting representative of healthcare facilities with typical artificial lighting. Sensor characterisation showed calibrated distance errors of -2.01 millimetres at a nominal 150-millimetre target and +0.61 millimetres at 400 millimetres, and tilt estimates of -29.60 and +30.59 degrees against nom
Open source S15tilt estimate
30.59
View original evidence
n took place at the ENEA Research Centre in Casaccia, inside the Technologies for Quality of Life Laboratory, in an indoor setting representative of healthcare facilities with typical artificial lighting. Sensor characterisation showed calibrated distance errors of -2.01 millimetres at a nominal 150-millimetre target and +0.61 millimetres at 400 millimetres, and tilt estimates of -29.60 and +30.59 degrees against nom
Open source S15
- code: not_reported
- weights: not_reported
- dataset: not_reported
Source excerpts and review record
Automatically extracted; no manual editorial approval recorded.
n took place at the ENEA Research Centre in Casaccia, inside the Technologies for Quality of Life Laboratory, in an indoor setting representative of healthcare facilities with typical artificial lighting. Sensor characterisation showed calibrated distance errors of -2.01 millimetres at a nominal 150-millimetre target and +0.61 millimetres at 400 millimetres, and tilt estimates of -29.60 and +30.59 degrees against nom
Open source S15
Robot NAO Learns to Plug Itself In With a Low-Cost Autonomous Charging Dock
Open source S1
The humanoid robot NAO, a familiar face in hospitals, classrooms and assisted-living facilities, has long been undermined by a mundane problem: its battery. Depending on how hard it works, the robot runs for roughly 90 to 120 minutes before needing a recharge that takes three to four hours through its standard interface, forcing caregivers to interrupt sessions and plug it in by hand. A new open-access study publishe
Open source S2
le 21. https://doi.org/10.1007/s44430-026-00036-2 Image Credits: AI Generated DOI: 10.1007/s44430-026-00036-2 Keywords: NAO robot, autonomous charging, docking station, socially assistive robots, time-of-flight sensors, healthcare robotics, IoT control, marker-based localisation, battery management, humanoid robotics, 3D printing, charging supervision
Open source S22
Source：Robotics — Robot learning news discovery · bioengineer.org