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Deep Learning

Visions for Robotics - Part 2

Part 2: In his very engaging follow-up lecture, Markus Vincze's continues to discuss tasks for robot vision (detection, grasping, and placing objects) in situated environments. In this talk, he demonstrates 3D object modelling and stresses the importance of robotics simulations, especially training robots the orientations of objects for grasping actions. He presents various approaches to object recognition and provides an introduction to deep learning. The talk is also suitable for beginners.

Knowledge representation and reasoning for robotic agents - Part 2

Part 2: In his follow-up lecture, Michael Beetz gives a short recap of his first talk before further exploring knowledge representation and reasoning for robotic agents. He focuses on one of the main problems of human-scale manipulation tasks for robotic systems, action description, when it comes to the performance of abstract tasks like "pour the water out". From "grasp the pot by the handles" to "tilt the pot around the axis between the handles" to "hold the lid while pouring", every action includes multiple intermediate tasks that have to be described in detail for the robot.