References of "Olivares Mendez, Miguel Angel 50002787"
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See detailHow to catch a space debris
Yalcin, Baris Can UL; Martinez Luna, Carol UL; Hubert Delisle, Maxime UL et al

Poster (2021, November 18)

The partnership between SpaceR and Spacety Luxembourg aims to develop cutting edge active space debris removal solutions that can be implemented into small cube sats The solution will take the advantage ... [more ▼]

The partnership between SpaceR and Spacety Luxembourg aims to develop cutting edge active space debris removal solutions that can be implemented into small cube sats The solution will take the advantage of latest advancements in many tech domains, such as gecko like sticky adhesives and energy efficient shape memory alloy materials. [less ▲]

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See detail5G-SpaceLab
Querol, Jorge UL; Abdalla, Abdelrahman UL; Bokal, Zhanna UL et al

Poster (2021, April 19)

The new phase of space exploration involves a growing number of human and robotic missions with varying communication and service requirements. Continuous, maximum coverage of areas where activities are ... [more ▼]

The new phase of space exploration involves a growing number of human and robotic missions with varying communication and service requirements. Continuous, maximum coverage of areas where activities are concentrated and orbiting missions (single spacecraft or constellations) around the Earth, Moon or Mars will be particularly challenging. The standardization of the 5G Non-Terrestrial Networks (NTN) has already begun [1], and nothing prevents 5G from becoming a common communications standard supporting space resource missions [2]. The 5G Space Communications Lab (5G-SpaceLab) is an interdisciplinary experimental platform, funded by the Luxembourg Space Agency and is part of the Space Research Program of SnT. The lab allows users to design and emulate realistic space communications and control scenarios for the next-generation of space applications. The capabilities of the 5G-SpaceLab testbed combine the experience of different disciplines including space communications, space and satellite mission design, and space robotics. The most relevant include the demonstration of SDR 5G NTN terminals including NB-IoT, emulation of space communications channel scenarios (e.g. link budget, delay, Doppler…), small satellite platform and payload design and testing, satellite swarm flight formation, lunar rover and robotic arm control and AI-powered telerobotics. Earth-Moon communications is one of the scenarios demonstrated in the 5G-SpaceLab. Bidirectional communication for the teleoperation of lunar rovers for near real-time operations including data collection and sensors feedback will be tested. AI-based approaches for perception and control will be developed to overcome communication delays and to provide safer, trustworthy, and efficient remote control of the rovers. [1] 3GPP Release 17 Timeline. [Online]. Available: https://www.3gpp.org/release-17 [2] Nokia, Nokia selected by NASA to build first ever cellular network on the Moon. [Online]. Available: https://www.nokia.com/about-us/news/releases/2020/10/19/nokia-selected-by-nasa-to-build-first-ever-cellular-network-on-the-moon/ [less ▲]

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See detailImplementation and validation of an event-based real-time nonlinear model predictive control framework with ROS interface for single and multi-robot systems
Dentler, Jan Eric UL; Kannan, Somasundar UL; Olivares Mendez, Miguel Angel UL et al

in 2017 IEEE Conference on Control Technology and Applications (CCTA) (2017, August 30)

This paper presents the implementation and experimental validation of a central control framework. The presented framework addresses the need for a controller, which provides high performance combined ... [more ▼]

This paper presents the implementation and experimental validation of a central control framework. The presented framework addresses the need for a controller, which provides high performance combined with a low-computational load while being on-line adaptable to changes in the control scenario. Examples for such scenarios are cooperative control, task-based control and fault-tolerant control, where the system's topology, dynamics, objectives and constraints are changing. The framework combines a fast Nonlinear Model Predictive Control (NMPC), a communication interface with the Robot Operating System (ROS) [1] as well as a modularization that allows an event-based change of the NMPC scenario. To experimentally validate performance and event-based adaptability of the framework, this paper is using a cooperative control scenario of Unmanned Aerial Vehicles (UAVs). The source code of the proposed framework is available under [2]. [less ▲]

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See detailReal-time graph-based SLAM in unknown environments using a small UAV
Annaiyan, Arun UL; Olivares Mendez, Miguel Angel UL; Voos, Holger UL

in 2017 International Conference on Unmanned Aircraft Systems (ICUAS); Miami 13-16 June 2017 (2017)

Autonomous navigation of small Unmanned Aerial Vehicles (UAVs) in cluttered environments is still a challenging problem. In this work, we present an approach based on graph slam and loop closure detection ... [more ▼]

Autonomous navigation of small Unmanned Aerial Vehicles (UAVs) in cluttered environments is still a challenging problem. In this work, we present an approach based on graph slam and loop closure detection for online mapping of unknown outdoor environments using a small UAV. Here, we used an onboard front facing stereo camera as the primary sensor. The data extracted by the cameras are used by the graph-based slam algorithm to estimate the position and create the graph-nodes and construct the map. To avoid multiple detections of one object as different objects and to identify re-visited locations, a loop closure detection is applied with optimization algorithm using the g2o toolbox to minimize the error. Furthermore, 3D occupancy map is used to represent the environment. This technique is used to save memory and computational time for the online processing. Real experiments are conducted in outdoor cluttered and open field environments.The experiment results show that our presented approach works under real time constraints, with an average time to process the nodes of the 3D map is 17.79ms. [less ▲]

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See detailA real-time model predictive position control with collision avoidance for commercial low-cost quadrotors
Dentler, Jan Eric UL; Kannan, Somasundar UL; Olivares Mendez, Miguel Angel UL et al

in IEEE Multi-Conference on Systems and Control (MSC 2016), Buenos Aires, Argentina, 2016 (2016, September 20)

Unmanned aerial vehicles (UAVs) are the future technology for autonomous fast transportation of individual goods. They have the advantage of being small, fast and not to be limited to the local ... [more ▼]

Unmanned aerial vehicles (UAVs) are the future technology for autonomous fast transportation of individual goods. They have the advantage of being small, fast and not to be limited to the local infrastructure. This is not only interesting for delivery of private consumption goods up to the doorstep, but also particularly for smart factories. One drawback of autonomous drone technology is the high development costs, that limit research and development to a small audience. This work is introducing a position control with collision avoidance as a first step to make low-cost drones more accessible to the execution of autonomous tasks. The paper introduces a semilinear state-space model for a commercial quadrotor and its adaptation to the commercially available AR.Drone 2 system. The position control introduced in this paper is a model predictive control (MPC) based on a condensed multiple-shooting continuation generalized minimal residual method (CMSCGMRES). The collision avoidance is implemented in the MPC based on a sigmoid function. The real-time applicability of the proposed methods is demonstrated in two experiments with a real AR.Drone quadrotor, adressing position tracking and collision avoidance. The experiments show the computational efficiency of the proposed control design with a measured maximum computation time of less than 2ms. [less ▲]

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