ISBN
Formato digital
979-13-87837-54-9
Fecha de publicación
06-10-2025
Licencia
D. R. © Copyright 2025. Alma Y. Alanis, Jorge Galvez, Omar Avalos, Eduardo Méndez-Palos, Jorge D. Rios, Adriana Peña Perez-Negron & Gabriel Martínez Soltero
Todos los contenidos de esta obra se comparten bajo la licencia Creative Commons Atri-bución/Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0). Esto implica que no está autorizado el uso comercial de la obra original ni de las eventuales obras derivadas, las cuales deberán distribuirse bajo la misma licencia que rige la obra original. No obstante, se permite a terceros compartir el contenido siempre y cuando se reconozca debidamente la autoría y la publicación original en esta editorial.
Óscar David Flores Ortega
Universidad de Guadalajara
Víctor Ernesto Moreno González
Universidad de Guadalajara
Francisco Javier Álvarez Padilla
Universidad de Guadalajara
0000-0003-0665-5895
Eduardo Méndez Palos
Universidad de Guadalajara
0000-0002-3267-024X
Jared Cortés Nuñez
Universidad de Guadalajara
Acerca de
Laparoscopic surgery is a minimally invasive technique that improves patient recovery, reduces post-surgical complications, and enhances precision. However, these procedures require an additional assistant to control the laparoscopic camera, which can be inefficient and increase fatigue for medical personnel. This paper presents an autonomous robotic arm that enhances control in laparoscopic surgeries by eliminating the need for a human camera assistant. The proposed system employs an advanced computer vision-based tool tracking method, ensuring continuous and precise tool centering in real time.
Unlike existing solutions such as the da Vinci Xi system, this approach leverages a lowcost, efficient, and adaptable mechanism for various laparoscopic procedures. The system integrates real-time object detection using YOLO and OpenCV, coupled with a robotic arm programmed to follow surgical tool movements. Our experimental results demonstrate improved camera stability, reduced procedural time, and enhanced surgeon comfort. This innovation represents a step towards intelligent surgical assistance systems, bridging the gap between autonomous robotics and minimally invasive procedures.
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