Abstract

Abstract
Robotics in agriculture faces several challenges, such as the unstructured characteristics of the environments, variability of luminosity conditions for perception systems, and vast field extensions. To implement autonomous navigation systems in these conditions, robots should be able to operate during large periods and travel long trajectories. For this reason, it is essential that simultaneous localization and mapping algorithms can perform in large-scale and long-term operating conditions. One of the main challenges for these methods is maintaining low memory resources while mapping extensive environments. This work tackles this issue, proposing a localization and mapping approach called VineSLAM that uses a topological mapping architecture to manage the memory resources required by the algorithm. This topological map is a graph-based structure where each node is agnostic to the type of data stored, enabling the creation of a multilayer mapping procedure. Also, a localization algorithm is implemented, which interacts with the topological map to perform access and search operations. Results show that our approach is aligned with the state-of-the-art regarding localization precision, being able to compute the robot pose in long and challenging trajectories in agriculture. In addition, we prove that the topological approach innovates the state-of-the-art memory management. The proposed algorithm requires less memory than the other benchmarked algorithms, and can maintain a constant memory allocation during the entire operation. This consists of a significant innovation, since our approach opens the possibility for the deployment of complex 3D SLAM algorithms in real-world applications without scale restrictions.

Abstract

Abstract

Abstract
The Open Laboratory of Interdisciplinary Experimentation (LAEI) had its 1st edition as UC "lnovPed" in the academic year 2018/2019, resulting from a proposal presented by professors from the Faculty of Arts, Faculty of Engineering and collaborators of the U. Porto. Imp1ementing the U.OpenLah concept and involving students from different degrees and scientific areas, LAEI has sought to develop basic skills and added value in creating digital experiences. Through theoretical exposition and an experimentation exercise in the field of digital content production or technologies for innovative digital content, creativity and project management, students share and implement the concepts and competences learned, including those of the scientific area of origin.

Abstract
In order to study the behavior and performance of a robot, building its simulation model is crucial. Realistic simulation tools using physics engines enable faster, more accurate and realistic testing conditions, without depending on the real vehicle. By combining legged and wheeled locomotion, hybrid vehicles are specially useful for operating in different types of terrains, both indoors and outdoors. They present increased mobility, versatility and adaptability, as well as easier maneuverability, when compared to vehicles using only one of the mechanisms. This paper presents the realistic simulation through the SimTwo simulator software of a hybrid legged-wheeled robot. It has four 3-DOF (degrees of freedom) legs combining rigid and non-rigid joints and has been fully designed, tested and validated in the simulated environment with incorporated dynamics.