Combined Sensing, Cognition, Learning, and Control for Developing Future Neuro-Robotics Systems: A Survey
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Neuro-robotics systems (NRSs) is the current state-of-the-art research with the strategic alliance of neuroscience and robotics. It endows the next generation of robots with embodied intelligence to identify themselves and interact with humans and environments naturally. Therefore, it needs to study the interaction of recent breakthroughs in brain neuroscience, robotics, and artificial intelligence where smarter robots could be developed by employing neural mechanisms and understanding brain functions. Recently, more sophisticated neural mechanisms of perception, cognition, learning, and control have been decoded, which investigate how to define and develop the “brain” for future robots. In this paper, a comprehensive survey is summarized by recent achievements in neuro-robotics, and some potential directions for the development of future neuro-robotics are discussed.
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.
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 | 0.001 | 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 it