Tom Krajnik edited this page Jan 3, 2017 · 9 revisions
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###Spatio Temporal Representations for Life-Long Mobile Robot Navigation

STRoLL is a research project aimed to create affordable robots capable of reliable long-term operation in outdoor, naturally-changing environments. In the end of this 3-year project, our robots will be able to understand the natural processes that change the environment appearance over time and use this knowledge to improve their ability to self-localise and navigate using only off-the-shelf, inexpensive sensors.

####Main objectives

The project has three main objectives: Development of spatio-temporal representations that will allow mobile robots to learn from their experience and understand the naturally-occurring changes in their environment. Development of the visual navigation, localization and mapping methods that will create, update and exploit the spatio-temporal models so that the robot will be capable of long-term autonomous navigation. Exhaustive dataset collection that will allow to benchmark the spatio-temporal models and navigation methods at the given testing sites throughout the entire project duration.

####Previous work

The STRoLL project will build upon the previous research aimed at robust visual navigation in environments that exhibit environment changes (see GRIEF, of SurfNav) and the concept of Frequency Map Enhancement FreMEn developed in the STRANDS project.

####Active tasks

  • establishing web presence,
  • data collection preparations,
  • kickoff meeting during April 2017.

####Project team

  • Dr. Tomas Krajnik, scientist-in-chief,
  • Tomas Vintr, data mining for inference of spatio-temporal representations.
  • PhD student_0, computer-vision methods robust to environment changes
  • PhD student_1, feature-based spatio-temporal exploration methods