Towards incremental autonomy framework for on-orbit vision-based grasping

in Proceedings of the International Astronautical Congress, IAC-2021 (2021, October 29)

This work presents a software-oriented autonomy framework that enables the incremental development of high robotic autonomy. The autonomy infrastructure in space applications is often cost-driven and ... [more ▼]

This work presents a software-oriented autonomy framework that enables the incremental development of high robotic autonomy. The autonomy infrastructure in space applications is often cost-driven and built for a narrow time/complexity domain. In domains like On-orbit Servicing Assembly and Manufacturing (OSAM), this prevents scalability and generalizability, motivating a more consistent approach for the incremental development of robotic autonomy. For this purpose, the problem of vision-based grasping is described as a building block for high autonomy of dexterous space robots. Subsequently, the need for a framework is highlighted to enable bottom-up development of general autonomy with vision-based grasping as the starting point. The preliminary framework presented here comprises three components. First, an autonomy level classification provides a clear description of the autonomous behavior of the system. The stack abstraction provides a general classification of the development layers. Finally, the generic execution architecture condenses the flow of translating a high-level task description into real-world sense-planact routines. Overall, this work lays down foundational elements towards development of general robotic autonomy for scalablity in space application domains like OSAM. [less ▲]

Enhancing Lunar Reconnaissance Orbiter Images via Multi-frame Super Resolution for Future Robotic Space Missions

in IEEE Robotics and Automation Letters (2021)

Lunar Surface Images Enhancement for Space Resources Localization and Extraction

Poster (2021, April 19)

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 ▲]

High-throughput biomass estimation in rice crops using UAV multispectral imagery

in Journal of Intelligent and Robotic Systems (2019), 96(3-4), 573--589

A Collaborative Vacuum Tool for Humans and Robots

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

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)

Towards autonomous detection and tracking of electric towers for aerial power line inspection

in 2014 International Conference on Unmanned Aircraft Systems (ICUAS) (2014)

A Hierarchical Tracking Strategy for Vision-Based Applications On-Board UAVs

in Journal of Intelligent & Robotic Systems (2013), 72(3-4), 517-539

In this paper, we apply a hierarchical tracking strategy of planar objects (or that can be assumed to be planar) that is based on direct methods for vision-based applications on-board UAVs. The use of ... [more ▼]

In this paper, we apply a hierarchical tracking strategy of planar objects (or that can be assumed to be planar) that is based on direct methods for vision-based applications on-board UAVs. The use of this tracking strategy allows to achieve the tasks at real-time frame rates and to overcome problems posed by the challenging conditions of the tasks: e.g. constant vibrations, fast 3D changes, or limited capacity on-board. The vast majority of approaches make use of featurebased methods to track objects. Nonetheless, in this paper we show that although some of these feature-based solutions are faster, direct methods can be more robust under fast 3D motions (fast changes in position), some changes in appearance, constant vibrations (without requiring any specific hardware or software for video stabilization), and situations in which part of the object to track is outside of the field of view of the camera. The performance of the proposed tracking strategy onboard UAVs is evaluated with images from realflight tests using manually-generated ground truthinformation, accurate position estimation using a Vicon system, and also with simulated data from a simulation environment. Results show that the hierarchical tracking strategy performs better than well-known feature-based algorithms and wellknown configurations of direct methods, and that its performance is robust enough for vision-in-theloop tasks, e.g. for vision-based landing tasks. [less ▲]