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Found 4 papers, 0 papers with code
Visual Spatial Attention and Proprioceptive Data-Driven Reinforcement Learning for Robust Peg-in-Hole Task Under Variable Conditions
In this study, we introduce a vision and proprioceptive data-driven robot control model for this task that is robust to challenging lighting and hole surface conditions.
Realtime Motion Generation with Active Perception Using Attention Mechanism for Cooking Robot
We tackled on the task of cooking scrambled eggs using real ingredients, in which the robot needs to perceive the states of the egg and adjust stirring movement in real time, while the egg is heated and the state changes continuously.
Deep Active Visual Attention for Real-time Robot Motion Generation: Emergence of Tool-body Assimilation and Adaptive Tool-use
The model incorporates a state-driven active top-down visual attention module, which acquires attentions that can actively change targets based on task states.
Enhanced precision of circadian rhythm by output system
Circadian rhythms are biological rhythms of approximately 24 h that persist even under constant conditions without environmental daily cues.
