Autonomous Robot Navigation Based on Clustering across Images

IEEE Robot. Autom. Lett.

Vintr

Molina

et al. 2019

Self Cite

This paper presents a novel method for introducing time into discrete and continuous spatial representations used in mobile robotics, by modelling long-term, pseudoperiodic variations caused by human activities. Unlike previous approaches, the proposed method does not treat time and space separately, and its continuous nature respects both the temporal and spatial continuity of the modeled phenomena. The method extends the given spatial model with a set of wrapped dimensions that represent the periodicities of observed changes. By performing clustering over this extended representation, we obtain a model that allows us to predict future states of both discrete and continuous spatial representations. We apply the proposed algorithm to several long-term datasets and show that the method enables a robot to predict future states of representations with different dimensions. The experiments further show that the method achieves more accurate predictions than the previous state of the art.

Section: Discussion Of Clusteringsupporting

confidence: 92%

Warped Hypertime Representations for Long-Term Autonomy of Mobile Robots

IEEE Robot. Autom. Lett.

Vintr

Molina

et al. 2019

Self Cite

“…In the future, we would like to overcome these limitations by using more sophisticated map building methods like the ones described in [34], [35]. Moreover, we would like to use publicly available maps instead of the human guided training run.…”

Section: Discussionmentioning

confidence: 99%

A simple visual navigation system for an UAV

International Multi-Conference on Systems, Sygnals &Amp; Devices

Nitsche²,

Pedre³

et al. 2012

Abstract-We present a simple and robust monocular camerabased navigation system for an autonomous quadcopter. The method does not require any additional infrastructure like radio beacons, artificial landmarks or GPS and can be easily combined with other navigation methods and algorithms. Its computational complexity is independent of the environment size and it works even when sensing only one landmark at a time, allowing its operation in landmark poor environments. We also describe an FPGA based embedded realization of the method's most computationally demanding phase.

“…Once the mapping is finished, the robot can autonomously traverse the learned path. Optionally, the gathered map quality might me be enhanced by methods [10], [11].…”

Section: A Ugv Navigationmentioning

confidence: 99%

Cooperative μUAV-UGV autonomous indoor surveillance

Saska

International Multi-Conference on Systems, Sygnals &Amp; Devices

Pfeucil

2012

Abstract-In this paper, we present a heterogenous UGV-UAV system cooperatively solving tasks of periodical surveillance in indoor environments. In the proposed scenario, the UGV is equipped with an interactive helipad and it acts as a carrier of the UAV. The UAV is a light-weight quadro-rotor helicopter equipped with two cameras, which are used to inspect locations inaccessible for the UGV. The paper is focused on the most crucial aspects of the proposed UAV-UGV periodical surveillance that are visual navigation, localization and autonomous landing that need to be done periodically. We propose two concepts of mobile helipads employed for correction of imprecise landing of the UAV. Beside the description of the visual navigation, relative localization and both helipads, a study of landing performance is provided. The performance of the complex system is proven by an experiment of autonomous periodical surveillance in a changing environment with presence of people.