Abstract
The Robot@Factory competition was recently included in Robotica, the main Portuguese Robotics Competition. This robot competition takes place in an emulated factory plant, where automatic guided vehicles (AGVs) must cooperate to perform tasks. To accomplish their goals, the AGVs must deal with localization, navigation, scheduling, and cooperation problems that must be solved autonomously. This robot competition can play an important role in education due to its inherent multidisciplinary approach, which can motivate students to bridge different technological areas. It can also play an important role in research and development, because it is expected that its outcomes will later be transferred to real-world problems in manufacturing or service robots. By presenting a scaled-down factory shop floor, this competition creates a benchmark that can be used to compare different approaches to the challenges that arise in this kind of environment. The ability to alter the environment, in some restricted areas, can usually promote the test and evaluation of different localization mechanisms, which is not possible in other competitions. This paper presents one of the possible approaches to build a robot capable of entering this competition. It can be used as a reference to current and new teams.

Abstract
Laser scanners are widely used in mobile robotics localization systems but, despite the enormous potential of its use, their high price tag is a major drawback, mainly for hobbyist and educational robotics practitioners that usually have a reduced budget. This paper presentes the modeling and simulation of a hacked Neato XV-11 Laser Scanner, having as motivation the fact that it is a very low cost alternative, when compared with the current available laser scanners. The modeling of a hacked Neato XV-11 Laser Scanner allows its realistic simulation and provides valuable information that can promote the development of better designs of robot localization systems based on this sensor. The sensor simulation was developed using SimTwo, which is a realistic simulation software that can support several types of robots.

Abstract
Develop ground robots for crop monitoring and harvesting in steep slope vineyards is a complex challenge. Because of two main reasons: harsh condition of the terrain and unstable localization accuracy got from Global Positioning Systems (GPS). This paper presents a hybrid SLAM (VineSLAM) considering low cost landmarks to increase the robot localization accuracy, robustness and redundancy on these steep slope vineyards. Also, we present a cost-effective robot to carry-out crop monitoring tasks in steep slope vineyard environment. Test results got in a simulated and in a real test case supports the proposed approach and robot.

Abstract
Crop monitoring and harvesting by ground robots on mountain vineyards is an intrinsically complex challenge, due to two main reasons: harsh conditions of the terrain and reduced time availability and unstable localization accuracy of the GPS system. In this paper is presented a cost effective robot that can be used on these mountain vineyards for crop monitoring tasks. Also it is explored a natural vineyard feature as the input of a standard 2D simultaneous localization and mapping approach (SLAM) for feature-based map extraction. In order to be possible to evaluate these natural features for mapping and localization purposes, a virtual scenario under ROS/Gazebo has been built and described. A low cost artificial landmark and an hybrid SLAM is proposed to increase the localization accuracy, robustness and redundancy on these mountain vineyards. The obtained results, on the simulation framework, validates the use of a localization system based on natural mountain vineyard features.

Abstract

Abstract