Abstract
In an era where robots are becoming an integral part of human quotidian activities, understanding how they function is crucial. Among the inherent building complexities, from electronics to mechanics, path planning emerges as a universal aspect of robotics. The primary contribution of this work is to provide an overview of the current state of robot path planning topics and a comparison between those same algorithms and its inherent characteristics. The path planning concept relies on the process by which an algorithm determines a collision-free path between a start and an end point, optimizing parameters such as energy consumption and distance. The quest for the most effective path planning method has been a long-standing discussion, as the choice of method is highly dependent on the specific application. This review consolidates and elucidates the categories of path planning methods, specifically classical or analytical methods, and computer intelligence methods. In addition, the operational principles of these categories will be explored, discussing their respective advantages and disadvantages, and reinforcing these discussions with relevant studies in the field. This work will focus on the most prevalent and recognized methods within the robotics path planning problem, being mobile robotics or manipulator arms, including Cell Decomposition, A*, Probabilistic Roadmaps, Rapidly-exploring Random Trees, Genetic Algorithms, Particle Swarm Optimization, Ant Colony Optimization, Artificial Potential Fields, Fuzzy, and Neural Networks. Following the detailed explanation of these methods, a comparative analysis of their advantages and drawbacks is organized in a comprehensive table. This comparison will be based on various quality metrics, such as the type of trajectory provided (global or local), the scenario implementation type (real or simulated scenarios), testing environments (static or dynamic), hybrid implementation possibilities, real-time implementation, completeness of the method, consideration of the robot's kinodynamic constraints, use of smoothing techniques, and whether the implementation is online or offline.

Abstract
This paper discusses the emerging field of robotics, particularly focusing on motion planning for robotic manipulators. It highlights the need for simplification and standardization in robot implementation processes. Among several tools available, the paper focuses on the MoveIt tool due to its compatibility, popularity, and community contributions. However, the paper acknowledges some resistance in developing new applications with MoveIt, especially for researchers and beginners. To address this, the paper introduces an efficient, modular action server for interacting with the MoveIt framework. This pipeline simplifies parameter reconfiguration and provides a general solution for the motion planning problem. It can calculate trajectories for robotic manipulators without environmental collisions using a single server request and supports operation in different modes. The server was tested on an Universal Robots UR10 manipulator, demonstrating its ability to quickly plan paths for two test operations: an object pick-and-place mission and a collision avoidance test. The results were positive, achieving the set goals with minimal user-server interaction. This work represents a significant step towards more efficient and user-friendly robotic manipulation.

Abstract
This article introduces Friday, a Mobile Manipulator (MoMa) solution designed at iiLab - INESC TEC. Friday is versatile and applicable in various contexts, including warehouses, naval shipyards, aerospace industries, and production lines. The robot features an omnidirectional platform, multiple grippers, and sensors for localisation, safety, and object detection. Its modular hardware and software system enhances functionality across different industrial scenarios. The system provides a stable platform supporting scientific advancements and meeting modern industry demands, with results verified in the aerospace, automotive, naval, and logistics.

Abstract
Emerging from a rich heritage, the shoe manufacturing industry stands as one of the world's most enduring and tradition-bound sectors. While renowned for their high-quality craftsmanship, countries like Portugal and Italy share the spotlight with those who focus on mass production methods. Regardless of their manufacturing model, both must adapt to the evolving competitive landscape by embracing innovative manufacturing techniques. Robotics has emerged as a transformative force within the shoe industry, offering a path towards enhanced working conditions for employees while simultaneously reducing reliance on manual labor and bolstering productivity. The main focus of this paper is the comprehensive literature review, which examines the advancements made by researchers in various stages of shoe production, including roughing, gluing, finishing, and lasting. This article sheds light on the industry's response to modernization and efficiency imperatives, providing a thorough understanding of robotics in shoe manufacturing automation. A case study on the real implementation and simulation of a robotic cell for sole roughing is also presented. The results revealed that the robotic cell maintains the production cadence.