2 citations · 4 across the 4 of their papers we have counts for
4 papers
Robotic Test Tube Rearrangement Using Combined Reinforcement Learning and Motion Planning
Hao Chen, Weiwei Wan, Masaki Matsushita +2
A combined task-level reinforcement learning and motion planning framework is proposed in this paper to address a multi-class in-rack test tube rearrangement problem. At the task l…
In-Rack Test Tube Pose Estimation Using RGB-D Data
Hao Chen, Weiwei Wan, Masaki Matsushita +2
Accurate robotic manipulation of test tubes in biology and medical industries is becoming increasingly important to address workforce shortages and improve worker safety. The detec…
Automatically Prepare Training Data for YOLO Using Robotic In-Hand Observation and Synthesis
Hao Chen, Weiwei Wan, Masaki Matsushita +2
Deep learning methods have recently exhibited impressive performance in object detection. However, such methods needed much training data to achieve high recognition accuracy, whic…
Arranging Test Tubes in Racks Using Combined Task and Motion Planning
Weiwei Wan, Takeyuki Kotaka, Kensuke Harada
The paper develops a robotic manipulation system to treat the pressing needs for handling a large number of test tubes in clinical examination and replace or reduce human labor. It…