3 accepted papers
Offline learning usually requires a large dataset for training. In this paper, we focus on vision-based robotic manipulation tasks and utilize certain task properties to achieve offline learning with a small dataset. We propose a two-stage agent consisting of a tentative decision stage and a correct…
In this paper, we propose a method for reinforcement learning-based laser welding control. Conventional methods apply standard reinforcement learning formulations to welding tasks, but we show that this formulation can minimize bead width or penetration depth errors only when the welding speed is co…
Container loading by a picking robot is an important challenge in the logistics industry. When designing such a robotic system, item picking and placing have been planned individually thus far. However, since the condition of picking an item affects the possible candidates for placing, it is prefera…