Abstract
One of the most important tasks for a mobile robot is to navigate in an environment. The path planning is required to design the trajectory that generates useful motions from the original to the desired position. There are several methodologies to perform the path planning. In this paper, a new method of approximate cells decomposition, called K-Framed Quadtrees is present, to which the algorithm A ? is applied to determine trajectories between two points. To validate the new approach, we made a comparative analysis between the present method, the grid decomposition, quadtree decomposition and framed quadtree decomposition. Results and implementation specifications of the four methods are presented. © 2018, Springer International Publishing AG.

Abstract
This paper presents a path planning method for pick-and-place operations with obstacles in the work environment. The method developed is designed to plan the motion of an anthropomorphic manipulator in cluttered environments. The graph search algorithm A* applied to the configuration free space is used to calculate the shortest path between two points avoiding collisions with obstacles and joint limitations. Applying this algorithm in a six dimension space presents some constraints related to memory consumption and processing time, which were tackled using configuration space partition and selecting neighbourhood cells, respectively. Using the configuration space makes it possible for the entire robot body to avoid collisions with obstacles. Moreover, the system implemented proves that applying A* in high dimension configuration spaces is possible with admissible results.

Abstract
The field of Robotics has become one of the most rapidly growing fields in the research and technological world. The development of flexible robots represents the possibility of them becoming a highly efficient operator in the industrial environment. Intelligent robots present key characteristics that enable the streamlining of automated processes associated to industry. Adding the adaptive component to such robots facilitates the design of solutions for a wide range of problems. Pick and Place operations have attracted considerable interest from the research and industrial community as they present one of the most effective solutions to typical problems such as handling or transportation. Another aspect to consider when developing a robotic solution for pick and place approaches is the methodology for recognition of the objects to be handled. In this paper, it will be presented a methodology that can be applicable to different scenarios in order to both identify the objects of a given scene and reply to the need of handling those objects. Furthermore it will be presented one specific case study that used the proposed methodology, the Amazon Picking Challenge - a challenge aiming to develop solutions for the complete automation of a dispatching warehouse. Our proposed methodology was built using the Robotic Operative System (ROS) framework and is based in three tiers: recognition, movement / actuation and control. ROS allows the decomplexation of typical problems associated to robotics as this framework promotes the development of modular and simple software that together fulfill the state-of-art requests of the industry. Since ROS is becoming an important tool in robotics, using a methodology developed in ROS allows for the development of a standard approach to pick and place operations. Another advantage of our methodology is the ability to have a robot safely and efficiently inserted in an unknown environment. This is possible due to adaptive control tier. Proposed improvements to currently available methods will be also described in this project. Throughout the document, the importance of this project and the development of novel robots will be described taken into consideration the need for robots in the industrial setting.

Abstract
The ionizing radiation is used in the nuclear medicine field during the execution of diagnosis exams. The continuous exposure of humans to the radiation may cause organs and tissues damage, being its severity dependent of the quantity of the radiation and the exposure time. The main objective of this work is to design a virtual environment to carry out the simulation of the several stages for the preparation of radioactive products based on the use of a robotic arm. In this work, the V-REP robotic simulation tool was used for the specification and development of the manipulation processes, without the need to consider the real manipulator, being timely and costly efficient. During this study, the preparation process of the dosages in the diagnostic exams was analyzed, being posteriorly translated into mechanical processes for a better perception. The materials and equipment needed were designed as virtual 3D models and posteriorly imported into the V-REP simulation platform in order to be distributed and programmed to achieve a closer approximation to reality.

Abstract
The new paradigms of Industry 4.0 demand the collaboration between robot and humans. They could help and collaborate each other without any additional safety unlike other manipulators. The robot should have the ability of acquire the environment and plan (or re-plan) on-the-fly the movement avoiding the obstacles and people. This paper proposes a system that acquires the environment space, based on a kinect sensor, performs the path planning of a UR5 manipulator for pick and place tasks while avoiding the objects, based on the point cloud from kinect. Results allow to validate the proposed system. © Springer International Publishing AG 2018.

Abstract
Some industries have critical areas (dangerous or hazardous) where the presence of a human must be reduced or avoided. In some cases, there are areas where humans should be replaced by robots. The present work uses a robot with differential drive to scan an environment with known and unknown obstacles, defined in 3D simulation. It is important that the robot be able to make the right decisions about its way without the need of an operator. A solution to this challenge will be presented in this paper. The control application and its communication module with a simulator or a real robot are proposed. The robot can perform the scan, passing through all the waypoints arranged in a grid. The results are presented, showcasing the robot’s capacity to perform a viable trajectory without human intervention. © Springer International Publishing AG 2018.