SORA Methodology for Multi-UAS Airframe Inspections in an Airport

in Drones (2021), 5(4 141),

Deploying Unmanned Aircraft Systems (UAS) in safety- and business-critical operations requires demonstrating compliance with applicable regulations and a comprehensive understanding of the residual risk ... [more ▼]

Deploying Unmanned Aircraft Systems (UAS) in safety- and business-critical operations requires demonstrating compliance with applicable regulations and a comprehensive understanding of the residual risk associated with the UAS operation. To support these activities and enable the safe deployment of UAS into civil airspace, the European Union Aviation Safety Agency (EASA) has established a UAS regulatory framework that mandates the execution of safety risk assessment for UAS operations in order to gain authorization to carry out certain types of operations. Driven by this framework, the Joint Authorities for Rulemaking on Unmanned Systems (JARUS) released the Specific Operation Risk Assessment (SORA) methodology that guides the systematic risk assessment for UAS operations. However, existing work on SORA and its applications focuses mainly on single UAS operations, offering limited support for assuring operations conducted with multiple UAS and with autonomous features. Therefore, the work presented in this paper analyzes the application of SORA for a Multi-UAS airframe inspection (AFI) operation, that involves deploying multiple UAS with autonomous features inside an airport. We present the decision-making process of each SORA step and its application to a multiple UAS scenario. The results shows that the procedures and safety features included in the Multi-AFI operation such as workspace segmentation, the independent multi-UAS AFI crew proposed, and the mitigation actions provide confidence that the operation can be conducted safely and can receive a positive evaluation from the competent authorities. We also present our key findings from the application of SORA and discuss how it can be extended to better support multi-UAS operations. [less ▲]

A Collaborative Vacuum Tool for Humans and Robots

in Proceedings of the Latin American Congress on Automation and Robotics (2019)

Safety Protocol for Collaborative Human-Robot Recycling Tasks

in IFAC-PapersOnLine (2019), 52(13), 2008--2013

Aerial mapping of rice crops using mosaicing techniques for vegetative index monitoring

in 2018 International Conference on Unmanned Aircraft Systems (ICUAS) (2018)

Towards image mosaicking with aerial images for monitoring rice crops

in Advances in Automation and Robotics Research in Latin America (2017)

HMPMR strategy for real-time tracking in aerial images, using direct methods

in Machine Vision and Applications (2014), 25(5), 1283-1308

The vast majority of approaches make use of features to track objects. In this paper, we address the tracking problem with a tracking-by-registration strategy based on direct methods. We propose a ... [more ▼]

The vast majority of approaches make use of features to track objects. In this paper, we address the tracking problem with a tracking-by-registration strategy based on direct methods. We propose a hierarchical strategy in terms of image resolution and number of parameters estimated in each resolution, that allows direct methods to be applied in demanding real-time visual-tracking applications. We have called this strategy the Hierarchical Multi-Parametric and Multi-Resolution strategy (HMPMR). The Inverse Composition Image Alignment Algorithm (ICIA) is used as an image registration technique and is extended to an HMPMR-ICIA. The proposed strategy is tested with different datasets and also with image data from real flight tests using an Unmanned Aerial Vehicle, where the requirements of direct methods are easily unsatisfied (e.g. vehicle vibrations). Results show that using an HMPMR approach, it is possible to cope with the efficiency problem and with the small motion constraint of direct methods, conducting the tracking task at real-time frame rates and obtaining a performance that is comparable to, or even better than, the one obtained with the other algorithms that were analyzed. [less ▲]

A supervised approach to electric tower detection and classification for power line inspection

in 2014 International Joint Conference on Neural Networks (IJCNN) (2014)

Visual Tracking, Pose Estimation, and Control for Aerial Vehicles

Doctoral thesis (2013)

A vision-based strategy for autonomous aerial refueling tasks

in Robotics and Autonomous Systems (2013), 61(8), 876--895

A hierarchical strategy for real-time tracking on-board uavs

in ICUAS 2012: 2012 International Conference on Unmanned Aircraft Systems (2012)