Lecture
Acquiring Data for Learning
Related lectures (344)
Robotics: Actuation and Mobility Analysis
Covers corrected exercises from the 2020 exam in the field of robotics, including topics such as accuracy, speed, DC motors, optimal gear ratio, dynamics of robot arms, encoders, and kinematics.
Center Pathet Generators for Agile Locomotion
Explores the use of Center Pathet Generators for agile locomotion in medium-sized robots.
Robotics Basics: Definitions and Applications
Introduces the basics of robotics, covering definitions, classifications, and statistics, and explores the evolution and applications of different types of robots.
Social Robots for Health & Education
Explores the use of social robots for health and education, emphasizing their unique influence on decision-making and learning interactions.
Robots: Safe Collaboration
Covers challenges and solutions for robots to work safely with humans, emphasizing adaptability and predictability.
Neural Networks: Logic and Applications
Explores the logic of neuronal function, the Perceptron model, deep learning applications, and levels of abstraction in neural models.
Computational Robot Design: Co-Optimization Insights
Explores computational robot design, emphasizing co-optimization insights and the use of graph grammars for efficient design.
Landscape and Generalisation in Deep Learning
Explores the challenges and insights of deep learning, focusing on loss landscape, generalization, and feature learning.
Vision-based robotic perception
Explores challenges and opportunities in vision-based robotic perception, covering topics like SLAM, place recognition, event cameras, and collaborative visual intelligence.
Optimization of Paper Planes
Explores the optimization of paper planes and soft structures for thrust generation.