Course content
This seminar for advanced users presents basic algorithms for the development of robotic systems that can independently perceive and manipulate objects in unstructured environments such as apartments, restaurants, supermarkets, etc. It addresses the complex and contemporary challenge of understanding and developing intelligent robotic manipulation. The seminar will cover basic methods of 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 (mainly force control and its variants) are discussed.
The seminar consists of a combination of introductory lectures and a reading group to discuss and learn advanced algorithmic approaches in robotics. After an introductory lecture on a new topic, students are assigned in small groups to a research paper fundamental to each topic (style may vary depending on class size). The students present the basic concept of the work in class and lead a discussion on the presented topics.
List of topics (not exhaustive):
Kinematics and dynamics refresher
Pick-and-place pipeline
Estimation of object position
Creation of grippers
Robot force control (stiffness, impedance, admittance)
Sampling-based motion
planning Trajectory optimization
Task and motion
planning Mobile manipulation
Prerequisites
Recommended:
Students should have basic knowledge of robotics and linear algebra. Also recommended is Fundamentals of Robotics (20-00-0735-iv Fundamentals of Robotics).
Online offers
moodle
This seminar for advanced users presents basic algorithms for the development of robotic systems that can independently perceive and manipulate objects in unstructured environments such as apartments, restaurants, supermarkets, etc. It addresses the complex and contemporary challenge of understanding and developing intelligent robotic manipulation. The seminar will cover basic methods of 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 (mainly force control and its variants) are discussed.
The seminar consists of a combination of introductory lectures and a reading group to discuss and learn advanced algorithmic approaches in robotics. After an introductory lecture on a new topic, students are assigned in small groups to a research paper fundamental to each topic (style may vary depending on class size). The students present the basic concept of the work in class and lead a discussion on the presented topics.
List of topics (not exhaustive):
Kinematics and dynamics refresher
Pick-and-place pipeline
Estimation of object position
Creation of grippers
Robot force control (stiffness, impedance, admittance)
Sampling-based motion
planning Trajectory optimization
Task and motion
planning Mobile manipulation
Prerequisites
Recommended:
Students should have basic knowledge of robotics and linear algebra. Also recommended is Fundamentals of Robotics (20-00-0735-iv Fundamentals of Robotics).
Online offers
moodle
- Lehrende: Georgia Chalvatzaki
Semester: WiSe 2022/23