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Event

Robotics III - Sensors and Perception in Robotics [SS232400067]

Type
lecture (V)
Präsenz
Term
SS 2023
SWS
2
Language
Deutsch/Englisch
Appointments
12
Links
ILIAS

Lecturers

Organisation

  • IAR Dillmann

Part of

Literature

Eine Foliensammlung wird im Laufe der Vorlesung angeboten.

Begleitende Literatur wird zu den einzelnen Themen in der Vorlesung bekannt gegeben.

Appointments

  • 20.04.2023 17:30 - 19:00 - Room: 50.34 Raum -102
  • 27.04.2023 17:30 - 19:00 - Room: 50.34 Raum -102
  • 04.05.2023 17:30 - 19:00 - Room: 50.34 Raum -102
  • 11.05.2023 17:30 - 19:00 - Room: 50.34 Raum -102
  • 25.05.2023 17:30 - 19:00 - Room: 50.34 Raum -102
  • 15.06.2023 17:30 - 19:00 - Room: 50.34 Raum -102
  • 22.06.2023 17:30 - 19:00 - Room: 50.34 Raum -102
  • 29.06.2023 17:30 - 19:00 - Room: 50.34 Raum -102
  • 06.07.2023 17:30 - 19:00 - Room: 50.34 Raum -102
  • 13.07.2023 17:30 - 19:00 - Room: 50.34 Raum -102
  • 20.07.2023 17:30 - 19:00 - Room: 50.34 Raum -102
  • 27.07.2023 17:30 - 19:00 - Room: 50.34 Raum -102

Note

The lecture supplements the lecture Robotics I with a broad overview of sensors used in robotics. The lecture focuses on visual perception, object recognition, simultaneous localization and mapping (SLAM) and semantic scene interpretation.  The lecture is divided into two parts:

In the first part a comprehensive overview of current sensor technologies is given. A basic distinction is made between sensors for the perception of the environment (exteroceptive) and sensors for the perception of the internal state (proprioceptive).

The second part of the lecture concentrates on the use of exteroceptive sensors in robotics. The topics covered include tactile exploration and visual data processing, including advanced topics such as feature extraction, object localization, simultaneous localization and mapping (SLAM) and semantic scene interpretation.

Learning Obejctives:

Students know the main sensor principles used in robotics and understand the data flow from physical measurement through digitization to the use of the recorded data for feature extraction, state estimation and environmental modeling.

 

Students are able to propose and justify suitable sensor concepts for common tasks in robotics.