Mina Samir Kamel

Our paper presented at RA-L/IROS2020 is now on arXiv! We proposed a unified motor thermal model learning, motor core temperature estimation, motor core control, and anomaly detection that, while applied to musculoskeletal robots, can be used for any type of robot. Title: Estimation and Control of Motor Core Temperature with Online Learning of Thermal Model Parameters: Application to Musculoskeletal Humanoids arXiv: https://lnkd.in/gua5rA-X

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Have you heard about non-traditional rolling robots? We geometrically model a Tensegrity eXploratory Robot (TeXploR) that allows for efficient rolling with stability. The static analysis shows that the robot is a hybrid system (four states) with non-linear dynamics. If you're interested, please check out Lauren Ervin's recently accepted paper at IEEE Robotics and Automation Society Letters (RA-L) : https://lnkd.in/emg54e32, and the Youtube video: https://lnkd.in/eRNkyVsU

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Ever wondered where to mount the #IMU on humans? We validate the #OpenSense framework for IMU-based joint angle estimation and furthermore analyse the framework's ability for sensor selection and optimal positioning during activities of daily living (ADL). We compared the joint kinematics of IMU-based #simulations with those of optical marker-based simulations and report differences in functional range of motion (fRoMD) estimation performance. Additionally, we analyse the influence of sensor count on joint angle estimation performance and derive the best sensor combinations. Sensor selection analyses showed that after three sensors for the lower limbs and four sensors for the complex shoulder joint, estimation error decreased only marginally. Global optimum (lowest RMSE) was obtained for five to eight sensors depending on the joint angle across all ADLs. Lowest errors were on average < 2° over all joint angles. Our results showed that the open-source OpenSense framework not only serves as a valid tool for realistic representation of joint kinematics and fRoM, but also yields valid results for IMU sensor selection for a comprehensive set of ADLs involving upper and lower limbs. The results can help researchers and developers to determine appropriate sensor positions and sensor configurations without the need for detailed biomechanical knowledge. Reference: Uhlenberg L and Amft O (2024). Where to mount the IMU? Validation of joint angle kinematics and sensor selection for activities of daily living. Front. Comput. Sci. 6:1347424. doi: 10.3389/fcomp.2024.1347424 Full text available here: https://lnkd.in/esHWBr3j 

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✈️ Want to understand the approach of Model-Based Design using Simulink? 🚁 The MathWorks Minidrone Competition is happening in Switzerland. This competition gives teams a fun way to learn how to design and build flight control algorithms for Minidrones using Simulink. Applications are due September 5th! Find out more below! #mathworks #minidronecompetition #matlab #simulink #robotics #drones https://spr.ly/6046YxyhO

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