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Abstract: This paper is concerned with learning to compute optimal robot trajectories for a given parametrized task. We propose to train a neural network ...
This paper is concerned with learning to compute optimal robot trajectories for a given parametrized task. We propose to train a neural network directly with ...
Incremental learning [3] and layered learning [4] have been proposed as suitable approaches to improve evolutionary robotic (ER) algorithms by subdividing ...
This paper is concerned with learning to compute optimal robot trajectories for a given parametrized task. We propose to train a neural network directly with ...
RoboCup 2023: Robot World Cup XXVI, 395-406, 2023. 2023. Learning Optimal Robot Ball Catching Trajectories Directly from the Model-based Trajectory Loss. A ...
Learning Optimal Robot Ball Catching Trajectories Directly from the Model-based Trajectory Loss. 2010 2nd International Asia Conference on Informatics in ...
Trajectories should be found which bring the end-effector into an orientation suitable for grasping, i.e. such that the target velocity vector is at some ...
In this paper, we present the Robot Anticipation Learning System (RALS) that accounts for the information obtained from observation of the thrower's hand ...
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Human-Robot Interaction is an important and challenging part of robotics as it re- quires high accuracy and sophisticated technology, along with safety.