A Passive-Based Physical Bipedal Robot With a Dynamic and Energy-Efficient Gait on the Flat Ground
Bibliographic record
Abstract
A passive walker is dynamic and energy efficient, but is always restricted to a downward gentle slope, and cannot walk on the flat ground. To design and build a bipedal walking robot, as dynamic and energy efficient as a passive walker, and still enable to walk on the flat ground, there is a need for a proper source of energy (actuation) to replace the gravitational energy input. Such an actuation system should allow the robot to walk a larger portion of a gait cycle all by its natural dynamics, and also, the actuation system does not have to suppress the natural dynamics of the robot. Therefore, in this paper, the authors present the design of a passive-based physical bipedal robot which can walk on the flat ground purely based on its natural dynamics (no control and no actuation) for a large portion of a gait cycle with a dynamic and highly energy-efficient gait. The robot has three internal degrees of freedom, i.e., the (active) hip and the two (passive) knees as well as the two round-feet rigidly connected to the two shanks. Only one compliant hip-actuation system is used to allow the robot to perform energy recovery as well as coordination between the energy input and the natural dynamics. The energy is injected at the hip and is stored in a torsional spring at the beginning of each gait cycle (40% of a gait cycle); such energy is then recovered to enable the robot walking forward entirely by its natural dynamics for the rest of that cycle (60% of a gait cycle). As a result, the robot can walk with a dynamic and highly energy-efficient gait on the flat ground with a Froude number of 0.176, a mechanical cost of transport of 0.086 , and a total cost of transport of 0.236, which are comparable to a human and the best available bipedal walking robots in the literature.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".