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ÇѱÛÁ¦¸ñ(Korean Title) ·Îº¿ ¹°µû¸£±â Á¶ÀÛ ½ºÅ³ ÇнÀÀ» À§ÇÑ ½Ã¹Ä·¹ÀÌ¼Ç ±â¹Ý ÈÆ·Ã ÇÁ·¹ÀÓ¿öÅ© ±¸Çö
¿µ¹®Á¦¸ñ(English Title) Implementation of Simulation based Training Framework for Learning Robotic Pouring Water Skill
ÀúÀÚ(Author) ±èÅ¿젠 Àå¹Î¼ö   ±èÀçÈ«   Taewoo Kim   Minsu Jang   Jaehong Kim  
¿ø¹®¼ö·Ïó(Citation) VOL 45 NO. 01 PP. 2565 ~ 2567 (2022. 06)
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(Korean Abstract)
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(English Abstract)
Imitation learning is one of the preferred approaches for learning complex and long-horizon robotic tasks, however, gathering the dataset for it requires lots of time and cost. To reduce such a cost, in this paper, we introduce our implementation result of training framework which is cost efficient in dataset collection. Through the GPU-accelerated simulator Isaac Gym and our object-oriented path generation method, we could achieve that gathering 50GB demonstration dataset within 25 minutes, in a randomized environment. We validated the dataset generated from our framework by robotic pouring water skill learning.
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