Design, Development and Control of a Hopping Machine – an Exercise in Biomechatronics
Bibliographic record
Abstract
Hopping is a complicated dynamic behaviour in the animal kingdom. Development of a hopping machine that can mimic the biomechanics of jumping in Homo sapiens is envisioned. In this context, the design, development and control of a cost-effective, pneumatically actuated, one-legged hopping machine were initiated at the University ofRegina in 2005. The pneumatic actuator has a simple design that employs an off-the-shelf on/off control valve which regulates the air pressure supplied to the hopper's body using a pulse width modulated (PWM) signal. The objective is to maintain a constant jumping height in the hopper after going through a finite number of hopping cycles. The mechanistic model of the system was investigated in full detail. This model facilitates: (1) the design of the actuating system, and (2) the synthesis and verification of different control strategies in a simulation environment prior to implementation in the real world. The movement of the hopper is supported by a vertical slide; therefore, the hopper can only jump in place. However, the proposed control strategy and the propulsion unit can be further utilised for stable hopping in a 3-D environment. A model-free Neuro-PD controller was then designed, trained and implemented on a real system. Simulation and experimentation showed promising results. This system can be used as an educational tool for teaching real-time control of hybrid and non-linear systems. It can be also used as a biomechatronics test bed to simulate the effect of different timings in firing action potentials in jump-causing leg muscles on achieving a desired jumping height in the animal kingdom.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".