This paper describes the mechanical design and a cognition system for a novel concept-of-camera robotic assistant. The system combines the advantages of intra-abdominal devices and autonomous camera navigation. The robotic assistant is composed of a magnetic intra-abdominal camera robot with two internal cable-driven degrees of freedom and an external robot that handles an external magnet. The intelligence of the robot is implemented in a cognitive architecture based on a long-term memory that stores the robot's knowledge and learning capabilities to improve the robot's behavior. The navigation strategy combines a reactive control based on instrument tracking and a proactive control based on predefined behaviors, depending on the actual state of the task. The robot's learning capabilities include a semantic customization, to adapt the camera's behavior to the surgeon's preferences, and reinforcement learning, to improve the camera navigation strategy. This paper details both the hardware implementation of the system and the software implementation in a robotic operating system architecture. The cognition system and the performance of the cable-driven mechanism have been validated with a set of in vitro experiments. Moreover, the camera robot has been evaluated through an in-vivo experiment in a pig.

(1) Background: Image acquisition systems based on videogrammetry principles are widely used across various research fields, particularly in mechanics, with applications ranging from civil engineering to biomechanics and kinematic analysis. This study presents the design, development, and validation of a low-cost, two-camera 3D videogrammetry system for the kinematic analysis of human motion. (2) Materials and Methods: Built using commercially available components and custom MATLAB^® (version 2019b) software, the system captures synchronized video streams and extracts precise 3D coordinates of markers. Its performance was validated against the Vicon^® (Vicon Nexus 1.7.1) system, a gold standard in musculoskeletal motion analysis. Comparative tests were conducted under static and dynamic conditions at varying working distances and velocities. (3) Results: Results demonstrate that the proposed system achieves high accuracy, with maximum measurement errors below 0.3% relative to Vicon^®, and similar repeatability (SD of approximately 0.02 mm in static conditions). Compared to manual caliper measurements, both vision systems yielded similar results, with errors ranging between 0.01% and 0.82%. (4) Conclusions: A low-cost, two-camera videogrametric system was validated, offering full transparency, flexibility, and affordability, making it a practical alternative for both clinical and research settings in biomechanics and human movement analysis, with potential to be extended to general kinematic analysis.

Este libro se ha elaborado como un recurso educativo introductorio a la biomecánica, principalmente destinado a estudiantes de Ingeniería de la Salud e Ingeniería Biomédica. En él, en primer lugar, se establecen unas bases para el entendimiento y la compresión de conceptos mecánicos aplicados al cuerpo humano, así como de los tipos de ensayos existentes en biomecánica y las estructuras presentes en el sistema musculoesquelético, tales como el hueso, los músculos, los tendones y ligamentos, y las articulaciones, y su forma de modelarlos mecánicamente. Posteriormente, en el segundo capítulo se exponen las diferentes magnitudes de interés en biomecánica, y los diferentes sensores que se pueden emplear para obtenerlas a través de los ensayos explicados en el primer capítulo.