Fully Autonomous Quadrotor: A Testbed Platform for Aerial Robotics Tasks

2012 ◽  
Author(s):  
Joao P. F. Guimaraes ◽  
Tania L. Laura ◽  
Armando S. Sanca ◽  
Alessandro N. Schildt ◽  
Michel S. de-Deus ◽  
...  
Keyword(s):  
Aerial Robotics

Detection and tracking of a landing platform for aerial robotics applications

2018 ◽  
Author(s):  
Miguel Saavedra Ruiz ◽  
Ana Maria Pinto Vargas ◽  
Victor Romero Cano
Keyword(s):  
Aerial Robotics ◽  
Detection And Tracking ◽  
Landing Platform

scholarly journals ARCog: An Aerial Robotics Cognitive Architecture

Robotica ◽  
2020 ◽  
pp. 1-20 ◽  
Author(s):  
Milena F. Pinto ◽  
Leonardo M. Honório ◽  
Andre L. M. Marcato ◽  
Mario A. R. Dantas ◽  
Aurelio G. Melo ◽  
...  
Keyword(s):  
Decision Making ◽  
Cognitive Architecture ◽  
Aerial Robotics ◽  
Sensors And Actuators ◽  
Cognitive Approach ◽  
Vehicle Architecture ◽  
Level Data ◽  
Intelligent Behavior ◽  
Key Issues ◽  
High Level

SUMMARY Efficient algorithm integration is a key issue in aerial robotics. However, only a few integration solutions rely on a cognitive approach. Cognitive approaches break down complex problems into independent units that may deal with progressively lower-level data interfaces, all the way down to sensors and actuators. A cognitive architecture defines information flow among units to produce emergent intelligent behavior. Despite the improvements in autonomous decision-making, several key issues remain open. One of these issues is the selection, coordination, and decision-making related to the several specialized tasks required for fulfilling mission objectives. This work addresses decision-making for the cognitive unmanned-aerial-vehicle architecture coined as ARCog. The proposed architecture lays the groundwork for the development of a software platform aligned with the requirements of the state-of-the-art technology in the field. The system is designed to provide high-level decision-making. Experiments prove that ARCog works correctly in its target scenario.

An execution control method for the Aerostack aerial robotics framework

2019 ◽  
Vol 20 (1) ◽  
pp. 60-75 ◽  
Author(s):  
Martin Molina ◽  
Alberto Camporredondo ◽  
Hriday Bavle ◽  
Alejandro Rodriguez-Ramos ◽  
Pascual Campoy
Keyword(s):  
Control Method ◽  
Aerial Robotics

scholarly journals Integrating Experimental Data Sets and Simulation Codes for Students into a MOOC on Aerial Robotics

2019 ◽  
Vol 52 (9) ◽  
pp. 50-55
Author(s):  
S. Bertrand ◽  
J. Marzat ◽  
G. Le Besnerais ◽  
A. Manzanera ◽  
C. Stoica Maniu ◽  
...  
Keyword(s):  
Experimental Data ◽  
Data Sets ◽  
Aerial Robotics ◽  
Simulation Codes

The USC AFV-I: a behavior-based entry in the 1994 International Aerial Robotics Competition

IEEE Expert ◽  
1995 ◽  
Vol 10 (2) ◽  
pp. 16-22 ◽  
Author(s):  
J.F. Montgomery ◽  
A.H. Fagg ◽  
G.A. Bekey
Keyword(s):  
Aerial Robotics ◽  
Behavior Based

Control and perception techniques for aerial robotics

2003 ◽  
Vol 36 (17) ◽  
pp. 31-39 ◽  
Author(s):  
A. Ollero
Keyword(s):  
Aerial Robotics

scholarly journals Structural inspection path planning via iterative viewpoint resampling with application to aerial robotics

2015 ◽  
Author(s):  
Andreas Bircher ◽  
Kostas Alexis ◽  
Michael Burri ◽  
Philipp Oettershagen ◽  
Sammy Omari ◽  
...  
Keyword(s):  
Path Planning ◽  
Aerial Robotics ◽  
Structural Inspection

scholarly journals Comparative Study of SLAM Techniques for UAV

2022 ◽  
Vol 12 (1) ◽  
pp. 67
Author(s):  
Abdul Rauf ◽  
Muhammad Jehanzeb Irshad ◽  
Muhammad Wasif ◽  
Syed Umar Rasheed ◽  
Nouman Aziz ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Linear System ◽  
Position Estimation ◽  
Ultra Wideband ◽  
Aerial Robotics ◽  
Military Operations ◽  
Localization And Mapping ◽  
Non Linear System ◽  
Gps System ◽  
Search Control

In the last few decades, the main problem which has attracted the attention of researchers in the field of aerial robotics is the position estimation or Simultaneously Localization and Mapping (SLAM) of aerial vehicles where the GPS system does not work. Aerial robotics are used to perform many tasks such as rescue, transportation, search, control, monitoring, and different military operations where the performance of humans is impossible because of their vast top view and reachability anywhere. There are many different techniques and algorithms which are used to overcome the localization and mapping problem. These techniques and algorithms use different sensors such as Red Green Blue and Depth (RGBD), Light Detecting and Range (LIDAR), Ultra-Wideband (UWB) techniques, and probability-based SLAM which uses two algorithms Linear Kalman Filter (LKF) and Extended Kalman filter (EKF). LKF consists of 5 phases and this algorithm is only used for linear system problems but on the other hand, EKF algorithm is also used for non-linear system. EKF is found better than LKF due to accuracy, practicality, and efficiency while dealing SLAM problem.

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