{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T13:07:13Z","timestamp":1765976833518,"version":"3.44.0"},"reference-count":29,"publisher":"Emerald","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,9,19]]},"abstract":"<jats:sec>\n                  <jats:title>Purpose<\/jats:title>\n                  <jats:p>The purpose of this paper is to present a high-precision method for localizing the Target Ball of an industrial robot, using Binocular Stereo Vision (BSV).<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Design\/methodology\/approach<\/jats:title>\n                  <jats:p>The steps for modeling the kinematics of a flexible robot include three steps. First, the kinematic model was developed, and robot motion tests were conducted, which is multiple sets of static joint angle motions. The kinematic parameters were calibrated based on a laser tracker and BSV, respectively. Second, the dynamics model was developed and operate the robot to perform motions, which is Fourier series excitation trajectories. The dynamics parameters were calibrated. Third, the static joint angles were brought into the dynamics model to calculate the external forces and moments of each joint. The stiffness parameters were calibrated.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Findings<\/jats:title>\n                  <jats:p>The experimental results show that after calibrating the kinematic parameters of the Target Ball, the Target Ball positioning error approximately 4.597\u2009mm. After calibrating the kinematic parameters of the Spherically Mounted Retro and stiffness parameters, the Target Ball positioning error is reduced from about 6.962\u2009mm to approximately 4.956\u2009mm, which is close to 4.597\u2009mm.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Research limitations\/implications<\/jats:title>\n                  <jats:p>The limitation of the approach is that, kinematic model and dynamics model are both required. Therefore, the high openness degree of robot is required, the robot needs to support path planning functions and joint moment extraction. However, some mature commercial robots do not support this.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Originality\/value<\/jats:title>\n                  <jats:p>In this paper, the stiffness model could effectively replace the calibration of the kinematic parameters of the load.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1108\/ir-07-2024-0317","type":"journal-article","created":{"date-parts":[[2025,2,10]],"date-time":"2025-02-10T03:20:41Z","timestamp":1739157641000},"page":"600-609","source":"Crossref","is-referenced-by-count":1,"title":["Target ball localization for industrial robots based on binocular stereo vision"],"prefix":"10.1108","volume":"52","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4965-2670","authenticated-orcid":true,"given":"Ming","family":"Li","sequence":"first","affiliation":[{"name":"Hefei University of Technology Department of Instrumentation Science and Opto-electronics Engineering, , 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