# Design and Simulation of a Vision-Based Automatic Trout Fish-Processing Robot
## 1 Introduction  
Trout, with the scientific name of _Oncorhynchus mykiss_, is from the salmon genus. The recent technology in the food industry is developed in different fields, such as fully automated and intelligent systems based on vision. Since the speed of the processing function, together with the accuracy and quality of the final product, is required, recent systems are equipped with vision-based equipment, especially in the products with different sizes and shapes. Fish sorting increases the final quality of the product but requires an initial investment and carries with it structural complexities [1]. In small and large fish centers, fish species in high demand are usually available in different sizes. In non-processed fresh fish, someprefer gutted fish; others opt for gutted and beheaded, or just in fillets. It should be noted that trout scales are finer than other species, and it can be processed without scaling. Due to the broad automation in industry, the need to design and manufacture automated devices with high capabilities in the fish and aquatic processing industries is of great importance. Because of the importance of fish consumption to the food industry, there is a need to design and develop fish-processing systems with higher capabilities than the current models. In fish-processing factories and fish supplying markets, it is necessary to properly stabilize the fish for cleaning operations. Due to the slippery skin and the low friction coefficient, it is usually challenging to control the fish constantly. To increase the system capacity, it is necessary to process the fish with functioning arms while the fish are passing in front of the processing tools. The initial modeling of the robots and mechanical systems together with simulation results in optimal real systems. In this condition not only are the links and joints and actual movements of the arms and actuators traced, but also the required forces and torques are determined in the most optimized condition. This needs defining the initial conditions of the friction coefficients, the movement limitations, required initial speeds and accelerations. In a study conducted by [PERSON] [2], the minimum length sliding mode control of a three degrees of freedom (DOF) Cartesian parallel robot was modeled and identified considering the virtual flexible links. In another study, kinematic optimal design of a partially compliant four-bar linkage using the elliptic integral solution was applied [3]. An analytical model of a compact flexure mechanism for translational motion together with the designing process was conducted by [PERSON] [4]. A conventional machine vision system (MVS) includes an image-capturing unit (camera), image processing unit, and statistical analysis [5]. Machine vision has been used in the field of aquaculture for classification, sex determination, and quality assessment. This non-destructive method was also applied in fish post-processing steps like removing unwanted parts and cutting the fillet edges. The following are examples of research conducted in this area. To adapt the fish cleaning system to the individual characteristics of each fish, it is necessary to provide special tools for cutting, gutting, cleaning, and gripping fish of different sizes. Machine vision as the main detection and processing tool was applied by [PERSON] for tuna growing stages [6]. This method was also applied to develop a fish counting algorithm while passing from the embedded system [7]. It was also applied for fish fillet quality and freshness assessment [8]. Fish freshness can be detected according to the color features of the eyes and the gills [9]. The fish length and size determination algorithm was developed by [PERSON] [10] and [PERSON] [11]. In other research, the size, direction, and heterogeneity of the fish were measured based on edge analysis to develop the tools for grading bass species [12]. The mechanical systems and cutting arms are designed in different fish-processing machines.