Development of a novel paediatric surgical assist robot for tissue manipulation in a narrow workspace
Bibliographic record
Abstract
Purpose Paediatric congenital esophageal atresia surgery typically requires delicate and dexterous operations in a narrow and confined workspace. This study aims to develop a novel robot assisted surgical system to address these challenges. Design/methodology/approach The proposed surgical robot consists of two symmetrical slave arms with nine degree of freedoms each. Each slave arm uses a rigid-dexterous configuration and consists of a coarse positioning manipulator and a distal fine operation manipulator. A small Selective Compliance Assembly Robot Arm (SCARA) mechanism was designed to form the main component of the coarse positioning unit, ensuring to endure large forces along the vertical direction and meet the operational demands. The fine positioning manipulator applied the novel design using flexible shafts and universal joints to achieve delicate operations while possessing a high rigidity. The corresponding kinematics has been derived and then was validated by a co-simulation that was performed based on the combined use of Adams and MATLAB with considering the real robot mass information. Experimental evaluations for the tip positioning accuracy and the ring transfer tasks have been performed. Findings The simulation was performed to verify the correctness of the derived inverse kinematics and demonstrated the robot’s flexibility. The experimental results illustrated that the end-effector can achieve a positioning accuracy within 1.5 mm in a confined 30 × 30 × 30 mm workspace. The ring transfer task demonstrated that the surgical robot is capable of providing a solution for dexterous tissue intervention in a narrow workspace for paediatric surgery. Originality/value A novel and compact surgical assist robot is developed to support delicate operations by using the dexterous slave arm. The slave arm consists of a SCARA mechanism to avoid experiencing overload in the vertical direction and a tool manipulator driven by flexible shafts and universal joints to provide high dexterity for operating in a narrow workspace.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".