# Parallel Fin Ray Soft Gripper with Embedded Mechano-Optical Force Sensor
## 5 Conclusions  
The development of soft robotics has significantly advanced across various sectors, including the industrial, medical, and agricultural domains. However, integrating force sensors into soft grippers remains challenging, as conventional sensors often compromise the flexibility and compliance of soft robotic systems. This study presents a parallel Fin Ray soft gripper with an embedded mechano-optical force sensor, enabling real-time force measurement without compromising adaptability. This proposed design aims to address the critical need for real-time sensing in soft grippers without compromising their flexibility, adaptability, or functionality. The proposed gripper, entirely fabricated using 3D-printing technology with PLA and TPE materials, is cost-effective, scalable, and adaptable, making it well suited to diverse robotic applications. Additive manufacturing enables precise customization and rapid prototyping, making the design highly adaptable to a wide range of applications. A key innovation is the integration of a mechano-optical force sensor directly within the gripper's Fin Ray structure, providing a compact and functional sensing mechanism for enhanced control and feedback during operation. The use of a syroid lattice pattern was specifically studied, yielding a linear force-response behavior with an \(R^{2}\) value of 0.96, capable of accurately measuring forces ranging from 0 N to 150 N. This combination of features makes the gripper particularly suited to tasks requiring precise contact force control, such as small fruit harvesting in the agricultural sector or pick-and-place operations in industry. Compared to other soft grippers with integrated force sensors, the proposed design offers a fully 3D-printed structure and demonstrates higher sensitivity in force measurements while preserving adaptability. Capacitive and resistive sensors are widely reported due to their widespread adoption [62; 63; 64; 65], but they face challenges related to hysteresis, limited dynamic range, and complex fabrication process. Many of these soft sensors require embedded conductive elements or multilayer manufacturing, whereas the mechano-optical sensor leverages a simpler fabrication process and provides a scalable solution. Although external wiring is necessary for power and data transmission, the optical sensing method minimizes additional electronics inside the soft structure, maintaining flexibility and compliance. By leveraging a syroid-patterned lattice for force distribution, this approach provides a reliable and efficient sensing mechanism for soft robotic applications. Future work will focus on accurately modeling soft gripper joints in the Robot Operating System (ROS) to improve simulation and real-world performance. Additionally, we will explore trajectory planning for the HoriRobot dual-arm platform, optimizing its integration for agricultural harvesting applications. Conceptualization, E.N. and R.F. ; methodology, E.N. ; validation, D.R.-N. and R.F. ; formal analysis, E.N. ; investigation, E.N. ; data curation, D.R.-N. and A.A.R.-G.; writing--original draft preparation, E.N. ; writing--review and editing, E.N and R.F. ; visualization, E.N. and A.A.R.-G.; supervision, R.F. ; principal investigator, R.F. All authors have read and agreed to the published version of the manuscript. The research leading to these results was supported in part by the following: (i) the Grant PID2020-116270 RB-I00 funded by MCIN/AEI/10.13039/501100011033; (ii) the Grant TED2021-132710B-I00 funded by MCIN/AEI/10.13039/501100011033 and by the \"European Union NextGenerationEU/PRTR\"; (iii) iRoboCity2030-CM, Robotica Inteligente para Ciudades Sostenibes (TEC-2024/TEC-62), funded by the Programas de Actividades I+D en Tecnologias en la Comunidad de Madrid; and (iv) CSIC under Grant 202350E072, Proyecto Intramural IAMMC-ROBI-II (Inteligencia Artificial y Mecantica Cognitiva para la Manipulacion Robotica Bimanual--2\({}^{\circ}\) Fase). Not applicable.