Existing grasp prediction approaches are mostly based on offline learnin...
This paper presents a novel method for model-free prediction of grasp po...
Detecting objects and estimating their 6D poses is essential for automat...
Robots often rely on a repertoire of previously-learned motion policies ...
Robotic manipulation is currently undergoing a profound paradigm shift d...
-based reinforcement learning (ERL) algorithms treat reinforcement
learn...
Sensor fusion can significantly improve the performance of many computer...
Meta-learning is widely used in few-shot classification and function
reg...
Many possible fields of application of robots in real world settings hin...
While classic control theory offers state of the art solutions in many
p...
Automated vehicles require a comprehensive understanding of traffic
situ...