50 citations · 214 across the 16 of their papers we have counts for
5 papers · 1 filter
Contact-Rich Manipulation of a Flexible Object based on Deep Predictive Learning using Vision and Tactility
Hideyuki Ichiwara, Hiroshi Ito, Kenjiro Yamamoto +2
We achieved contact-rich flexible object manipulation, which was difficult to control with vision alone. In the unzipping task we chose as a validation task, the gripper grasps the…
How to select and use tools? : Active Perception of Target Objects Using Multimodal Deep Learning
Namiko Saito, Tetsuya Ogata, Satoshi Funabashi +2
Selection of appropriate tools and use of them when performing daily tasks is a critical function for introducing robots for domestic applications. In previous studies, however, ad…
Embodying Pre-Trained Word Embeddings Through Robot Actions
Minori Toyoda, Kanata Suzuki, Hiroki Mori +2
We propose a promising neural network model with which to acquire a grounded representation of robot actions and the linguistic descriptions thereof. Properly responding to various…
Spatial Attention Point Network for Deep-learning-based Robust Autonomous Robot Motion Generation
Hideyuki Ichiwara, Hiroshi Ito, Kenjiro Yamamoto +2
Deep learning provides a powerful framework for automated acquisition of complex robotic motions. However, despite a certain degree of generalization, the need for vast amounts of…
In-air Knotting of Rope using Dual-Arm Robot based on Deep Learning
Kanata Suzuki, Momomi Kanamura, Yuki Suga +2
In this study, we report the successful execution of in-air knotting of rope using a dual-arm two-finger robot based on deep learning. Owing to its flexibility, the state of the ro…