Multi-rate Control Architectures for Dextrous Haptic Rendering in Cooperative Virtual Environments
Bibliographic record
Abstract
This paper is concerned with haptic simulation in multi-user virtual environments in which the users can haptically interact in a shared virtual world from separate workstations over an Ethernet local-area Network (LAN). High-fidelity haptic rendering requires a minimum control update rate of 1000Hz which is beyond the capability of popular network protocols such as the UDP and TCP/IP. Consequently, a multi-rate control strategy is adopted in which local force-feedback loops are executed at higher rates than data packet transmission between the user workstations. Two control architectures, i.e. centralized and distributed, are presented and their stability margins are compared. Two methods for mathematical modelling and analysis of the proposed multi-rate haptic control systems are examined. Analytical and experimental results demonstrate that the distributed control architecture is superior to the centralized controller from performance and stability perspectives. This is confirmed through experiments with a dual-user dual-finger haptic rendering platform.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".