Abstract
The increase of the world population and a decrease in agricultural labour availability have motivated research robotics in the agricultural field. This paper aims to analyze the state of the art related to manipulators used in the agricultural robotics field. Two pruning and seven harvesting manipulators were reviewed and are analyzed. The pruning manipulators were used in two different scenarios: (i) grapevines and (ii) apple trees. These manipulators showed that a light-controlled environment could reduce visual errors and that prismatic joints on the manipulator are advantageous to obtain a higher reach. The harvesting manipulators were used for 5 different products: (i) strawberries, (ii) tomatoes, (iii) apples, (iv) sweet-peppers and (v) iceberg lettuce. The harvesting manipulators showed that a different kinematic configuration is required for different end-effectors, as some end-effectors only require horizontal movements and others require more degrees of freedom to reach and grasp the target. This work will support new developments of novel solutions related to agricultural robotic grasping and manipulation.

Abstract
For remaining competitive in the current industrial manufacturing markets, coating companies need to implement flexible production systems for dealing with mass customization and mass production workflows. The introduction of robotic manipulators capable of mimicking with accuracy the motions executed by highly skilled technicians is an important factor in enabling coating companies to cope with high customization. However, there are some limitations associated with the usage of a fully automated system for coating applications, especially when considering customized products of large dimensions and complex geometry. This paper addresses the development of a collaborative coating cell to increase the flexibility and efficiency of coating processes. The robot trajectory is taught with an intuitive programming by demonstration system, in which an icosahedron marker with multicoloured LEDs is attached to the coating tool for tracking its trajectories using a stereoscopic vision system. For avoiding the construction of fixtures and allowing the operator to freely place products within the coating work cell, a modular 3D perception system was developed, relying on principal component analysis for performing the initial point cloud alignment and on the iterative closest point algorithm for 6 DoF pose estimation. Furthermore, to enable safe and intuitive human-robot collaboration, a non-intrusive zone monitoring safety system was employed to track the position of the operator in the cell.

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Correction to: M. F. Silva et al. (Eds.): Robot 2019: Fourth Iberian Robotics Conference, AISC 1092, https://doi.org/10.1007/978-3-030-35990-4 The original version of the book was inadvertently published with incomplete information in the Organization page of the front matter, which has now been included. The book has been updated with the change. © Springer Nature Switzerland AG 2020.

Abstract
Industrial robots are a technology which is highly present in industry and can perform several tasks, namely machining activities. Different than CNC machines, which work with G-code and have available several software applications to generate the machine code, there is a lack of software for robotic arms, in addition to each application depending on its own language and software. This work studied a way to use different robotic arms for 3D part machining processes, to perform 3D objects reconstruction obtained through a low-cost 3D scanner. Dealing with the 3D reconstruction by integrating 3D acquisition and robotic milling with software available on the market, this paper presents a system that acquires and reconstructs a 3D object, in order to seek greater flexibility with lower initial investments and checking the applicability of robot arm in these tasks. For this, a 3D object is scanned and imported to a CAD/CAM software, to generate the machining toolpath, and a software application is used to convert the G-code into robot code. Several experiments were performed, using an ABB IRB 2600 robot arm, and the results of the machining process allowed to validate the G-code conversion and milling process using robotic arms, according to the proposed methodology.