Bionote
Shaoxiong Yao is a fourth-year PhD student in Computer Science at the University of Illinois Urbana-Champaign, advised by Prof. Kris Hauser. His research focuses on tactile perception for deformable objects (e.g., plants) and developing robotic manipulation frameworks for agriculture. His work has been published at ICRA and CoRL.
Presentation Abstract
Fruit monitoring plays an important role in crop management, and rising global fruit consumption combined with labor shortages necessitates automated monitoring with robots. However, occlusions from plant foliage often hinder accurate shape and pose estimation. Therefore, we propose an active fruit shape and pose estimation method that physically manipulates occluding leaves to reveal hidden fruits. This paper introduces a framework that plans robot actions to maximize visibility and minimize leaf damage. We developed a novel scene-consistent shape completion technique to improve fruit estimation under heavy occlusion and utilize a perception-driven deformation graph model to predict leaf deformation during planning. Experiments on artificial and real sweet pepper plants demonstrate that our method enables robots to safely move leaves aside, exposing fruits for accurate shape and pose estimation, outperforming baseline methods.
Co-Authors: Sicong Pan, Maren Bennewitz, Kris Hauser