High-speed autonomous quadrotor navigation through visual and inertial paths
| Autor: | Stergios I. Roumeliotis, Tien Do, Luis C. Carrillo-Arce |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
0209 industrial biotechnology
Focus (computing) Inertial frame of reference Computer science business.industry Applied Mathematics Mechanical Engineering 02 engineering and technology Visual servoing 020901 industrial engineering & automation Artificial Intelligence Modeling and Simulation 0202 electrical engineering electronic engineering information engineering Graph (abstract data type) 020201 artificial intelligence & image processing Computer vision Artificial intelligence Electrical and Electronic Engineering business Software |
| Zdroj: | The International Journal of Robotics Research. 38:486-504 |
| ISSN: | 1741-3176 0278-3649 |
| DOI: | 10.1177/0278364918786575 |
| Popis: | This paper addresses the problem of autonomous quadrotor navigation within indoor spaces. In particular, we focus on the case where a visual map of the area, represented as a graph of linked images, is constructed offline (from visual and potentially inertial data collected beforehand) and used to determine visual paths for the quadrotor to follow. In addition, during the actual navigation, the quadrotor employs both wide- and short-baseline random sample consensuses (RANSACs) to efficiently determine its desired motion toward the next reference image and handle special motions, such as rotations in place. In particular, when the quadrotor relies only on visual observations, it uses the 5pt and 2pt algorithms in the wide- and short-baseline RANSACs, respectively. On the other hand, when information about the gravity direction is available, significant gains in speed are realized by using the 3pt+1 and 1pt+1 algorithms instead. Lastly, we introduce an adaptive optical-flow algorithm that can accurately estimate the quadrotor’s horizontal velocity under adverse conditions (e.g., when flying over dark, textureless floors) by progressively using information from more parts of the images. The speed and robustness of our algorithms are evaluated experimentally using a commercial-off-the-shelf quadrotor navigating in the presence of dynamic obstacles (i.e., people walking) along lengthy corridors and through tight corners, as well as across building floors via poorly lit staircases. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|