{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T05:11:51Z","timestamp":1788757911521,"version":"build-2803163510"},"reference-count":36,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T00:00:00Z","timestamp":1788652800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T00:00:00Z","timestamp":1788652800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["52475024"],"award-info":[{"award-number":["52475024"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Robotics Computer Surgery"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Reliable force perception is critical in robot\u2010assisted minimally invasive surgery. However, constraints in end\u2010effector size and complexity of the surgical environment hamper the integration of force sensors for direct feedback.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this study, an adaptive grid search algorithm with dynamic step\u2010size adjustment is proposed to optimise the Hunt\u2013Crossley (HC) model parameters for precise force estimation in robotic applications. The method continuously adjusts the step size based on real\u2010time estimation error, thereby enabling efficient investigation of the parameter space and refined optimisation near the optimal solution.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Experimental results show that the proposed method improves force estimation accuracy, with a reduction in Maximum Error (ME) of at least 25%, and reductions in Root Mean Square Error (RMSE) and Average Error (AE) of at least 30% compared to conventional fixed\u2010step approaches.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>These improvements enhance operational safety and also achieve the balance between computational efficiency and perception accuracy.<\/jats:p>\n                  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