A Dual-Arm 7-Degrees-of-Freedom Haptics-Enabled Teleoperation Test Bed for Minimally Invasive Surgery
Bibliographic record
Abstract
This paper describes a dual-arm teleoperation (master-slave) system which has been developed to explore the effect of haptics in robotics-assisted minimally invasive surgery (RAMIS). This setup is capable of measuring forces in 7 degrees of freedom (DOF) and fully reflecting them to the operator through two 7-DOF haptic interfaces. An application of the test bed is in enabling the evaluation of the effect of replacing haptic feedback by other sensory cues such as visual representation of haptic information (sensory substitution). This paper discusses the design rationale, kinematic analysis and dynamic modeling of the robot manipulators, and the control system developed for the setup. Using the accurate model developed in this paper, a highly transparent haptics-enabled system can be achieved and used in robot-assisted telesurgery. Validation results obtained through experiments are presented and demonstrate the correctness and effectiveness of the developed models. The application of the setup for two RAMIS surgical tasks, a suture manipulation task and a tumor localization task, is described with different haptics modalities available through the developed haptics-enabled system for each application.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".