1 citations · 1 across the 4 of their papers we have counts for
4 papers
VFILC: Accurate Frequency Extrapolations in Imitation Learning via Sampling Frequency ILC
Nozomu Masuya, Toshiaki Tsuji, Sho Sakaino
Conventional neural network (NN)-based imitation learning methods for variable-speed motion either restricted their scope to interpolated speeds, or generated unpredictable motions…
Motion Generation for Food Topping Challenge 2024: Serving Salmon Roe Bowl and Picking Fried Chicken
Koki Inami, Masashi Konosu, Koki Yamane +6
Although robots have been introduced in many industries, food production robots are yet to be widely employed because the food industry requires not only delicate movements to hand…
Variable-Speed Teaching-Playback as Real-World Data Augmentation for Imitation Learning
Nozomu Masuya, Hiroshi Sato, Koki Yamane +3
Because imitation learning relies on human demonstrations in hard-to-simulate settings, the inclusion of force control in this method has resulted in a shortage of training data, e…
Variable-Frequency Imitation Learning for Variable-Speed Motion
Nozomu Masuya, Sho Sakaino, Toshiaki Tsuji
Conventional methods of imitation learning for variable-speed motion have difficulty extrapolating speeds because they rely on learning models running at a constant sampling freque…