External force observer for medium-sized humanoid robots
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we introduce a method to estimate the magnitude of an external force applied on a humanoid robot. The approach does not require using force/torque sensors but instead uses measurements from commonly available force-sensing resistors (FSR) inserted under the feet of the humanoid robot. This approach is particularly interesting for affordable medium-sized humanoid robots such as Nao and Darwin-OP. The main idea is to use a simplified dynamic model of a linear inverted pendulum model (LIPM) subjected to an external force, and the information from the robot inertial measurement unit (IMU) and FSR sensors. The proposed method was validated on a Nao humanoid robot to estimate the external force applied in the sagittal plane through two experimental scenarios, and the results pointed out the efficiency of the proposed observer.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it