Real-Time Wide-Baseline Place Recognition Using Depth Completion
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Designing effective behavioral controllers for mobile robots can be difficult and tedious; this process can be circumvented by using online learning techniques which allow robots to generate their own controllers online in an automated fash- ion. In multi- ...
This doctoral thesis deals with an open subproblem of robot navigation, namely simultaneous localization and mapping (SLAM) in three-dimensional space. The goal is to develop a system which is capable of localizing a mobile robot in a reliable way and at t ...
Aerial swarms have the potential to search for forest fires, chemical plumes or victims and serve as communication and sensor networks in the sky. Flying robots are interesting for such applications because they are fast, can easily overcome difficult terr ...
Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of higher flexibility and association of semantics to the model. Ideally, a place rec ...
Swarms of flying robots are a promising alternative to ground-based robots for search in indoor environments with advantages such as increased speed and the ability to fly above obstacles. However, there are numerous problems that must be surmounted includ ...
An important competence for a mobile robot system is the ability to localize and perform context interpretation. This is required to perform basic navigation and to facilitate local specific services. Usually localization is performed based on a purely geo ...
ntegrating information coming from different sensors is a fundamental capability for autonomous robots. For complex tasks like topological localization, it would be desirable to use multiple cues, possibly from different modalities, so to achieve robust pe ...
A mapping system by vision-aided inertial navigation was developed for areas where GNSS signals are unreachable. In this framework, a methodology on the integration of vision and inertial sensors is presented, analysed and tested. The system employs the me ...
Learning from experience and adapting to changing stimuli are fundamental capabilities for artificial cognitive systems. This calls for on-line learning methods able to achieve high accuracy while at the same time using limited computer power. Research on ...
Tracking of miniature robotic platforms involves major challenges in image recognition and data association. We present our 3-year effort into developing the platform-independent, easy-to-use, and robust tracking software SwisTrack, which is tailored to re ...
