Analysis and compensation of calibration errors in a multi-robot surgical platform
| Autor: | Matteo Giussani, Lorenzo Molinari Tosatti, Federico Vicentini, Paolo Magnoni |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Robot kinematics
Kinematics Robot calibration Computer science Calibration (statistics) business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Workspace Transforms Compensation (engineering) Manipulators Calibration Robot sensing systems Robot Computer vision Artificial intelligence business Simulation Iterative closest point algorithm |
| Zdroj: | IEEE/RSJ International Conference on Intelligent Robots and Systems 2015, pp. 3633–3640, Hamburg, September 28-October 02, 2015 info:cnr-pdr/source/autori:Vicentini Federico; Magnoni Paolo; Giussani Matteo; Molinari Tosatti Lorenzo/congresso_nome:IEEE%2FRSJ International Conference on Intelligent Robots and Systems 2015/congresso_luogo:Hamburg/congresso_data:September 28-October 02, 2015/anno:2015/pagina_da:3633/pagina_a:3640/intervallo_pagine:3633–3640 IROS |
| Popis: | A case study of multi-robot platform calibration is reported in the domain of robot-assisted neurosurgery. The robot system is composed of a hybrid parallel kinematic machine and 2 KUKA LWR arms and is dedicated to awake surgery with head motion compensation. The target accuracy is sub-millimeter. Calibration errors are known to cumulate along the kinematic loops in the system, so a method of volumetric compensation of inaccuracies is applied. Configuration-dependent compensation homogeneous transforms populate a look-up table trained offline for a set of discrete subregions of the workspace. At runtime, the compensation is applied to the robot motion so to reach an end-to-end static accuracy distributed with a median 0.75 mm and below 1 mm for the 95% of tests, with a 1∶36 reduction factor from the default calibration conditions. |
| Databáze: | OpenAIRE |
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