Robotic Manipulation

Probabilistic Multi-View Fusion  of Active Stereo Depth Maps

fusion.png

Jun Yang, Dong Li and Steven L. Waslander. 

IEEE Robotics and Automation Letters (RA-L), 2021

Accepted

The reliable fusion of depth maps from multiple viewpoints has become an important problem in many 3D reconstruction pipelines. In this work, we investigate its impact on robotic bin-picking tasks such as 6D object pose estimation. In this work, we propose a novel probabilistic framework for scene reconstruction in robotic bin-picking. Based on active stereo camera data, we first explicitly estimate the uncertainty of depth measurements, and incorporated into a probabilistic model for incrementally updating the scene. To extensively evaluate different fusion methods, we constructed ROBI (Reflective Objects in BIns), a multi-view dataset consisting of reflective objects in bin-picking scenes. ​The ROBI dataset will be released.

ROBI Dataset

  • The dataset is available here.