FB20 Computer Science · 6 CP (estimated from SWS) · Offered in WiSe 2025/26
Average of averages
2.03
Every semester counts equally, whatever its size.
Pooled average
2.03
Weighted by cohort size — what an arbitrary student across all semesters scored.
Pass rate
82%
Share of results at 4.0 or better. 4.0 is the last passing grade.
Semesters with data
1
The German scale runs 1.0 (best) to 4.0 (last pass), with 5.0 as fail. There is no 4.3.
Missing (medical excuse): 1Reported Sep 5, 2026
No ratings yet — be the first.
Your vote is stored against a random id in this browser. No account, nothing that identifies you.
This course introduces fundamental algorithmic approaches for creating robot systems that can autonomously manipulate physical objects in unstructured environments such as homes. We will cover basic principles for endowing autonomous robots with planning, perception, and decision-making capabilities, i.e., topics include perception (including approaches based on deep learning and approaches based on 3D geometry), planning (robot kinematics and trajectory generation, collision-free motion planning, task-and-motion planning, and planning under uncertainty), as well as dynamics and control for adaptive and reactive manipulation. Tentative list of topics: Topology in robotics and rigid body motions Refresher on forward, inverse kinematics and dynamics Differential kinematics and optimization Geometric perception and object pose detection Object pose estimation and tracking and multi-sensor fusion Grasp generation and grasp evaluation Trajectory Optimization Search and Sampling-based motion planning Force control Visuomotor policies and intuitive physics Task and motion planning and belief-space planning Practical exercises will guide understanding fundamental mathematical and algorithmic principles for enabling robotic manipulators to perceive their environment, estimate the current state of the robot itself and the robots or humans in their surroundings, and create a strategy for executing various tasks that involve autonomously manipulating objects in cluttered scenes.
No exam date published.
Add to plannerTimes, rooms and details come from TUCaN and may be out of date. Report something wrong