Multi-contact Stability of Multi-Legged Robots Operating in Unstructured Spaces
Bibliographic record
Abstract
According to International Labor Organization, about 2.3 million work-related incidents occur annually globally. In Canada, this number is also high with 3000 people being disabled due to work-related accidents annually. One approach to reduce these numbers is providing workers with robotic tools in high-risk workspaces. The approach taken in this research is to develop an effective multi-contact locomotion system for multi-legged robots enabling them to operate in unstructured spaces. The solution allows humanoids to use not only their feet but also any other parts of their body to contact the environment and enhance their locomotion. Within the literature, the most relevant methods used today provide effective results for robots operating on structured surfaces such as stairs and hard flat surfaces. Although effective, such methods are not useful for unstructured surfaces, or in cases where robots must employ a multi-contact approach in their locomotion. In this regard, a modified version of Contact Wrench Set (CWS) method was developed in this research utilizing three arbitrary contact points to demonstrate the physics of contact and test for stability. The developed method can be utilized for a variety of terrains and environments such as mines and industrial facilities extending the past capabilities of the CWS formulation. The development of the proposed theoretical formulation is presented, and a novel visualization tool used to show the stability severity level of stable modes is also provided. Thorough verification of the new formulations was investigated using a comprehensive set of computer simulations tests via a multi-body dynamic simulation software. In this analysis, different types of surfaces with different characteristics have been evaluated. The results of the simulation show a reasonable consistency between the theoretical model and simulation for both flat and sloped surfaces. Finally, the method was experimentally tested on a life-size humanoid via the development of a set of Robot Operating System (ROS) packages. The contribution of this research is the development of novel stability mechanisms for humanoids locomotion enhancing the deployment of multi-legged robots in hazardous spaces, thus reducing the number of work-related casualties and injuries.
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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) | 0.001 | 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) | 0.002 | 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".