Acquiring Data for Learning: Modern Approaches and Challenges
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Explores challenges and opportunities in vision-based robotic perception, covering topics like SLAM, place recognition, event cameras, and collaborative visual intelligence.
Explores the vision of BeLearn in digital education transformation and challenges, emphasizing the importance of adapting to digital changes in education.
Delves into physical and social factors in human-robot interaction, covering topics like joint overloading torque estimation and adaptive control strategies.
Explores Bayesian disturbance injection for robust imitation in robot learning, demonstrating its effectiveness in reducing error compounding and achieving high task achievement.
