Bionote
Sicong Pan is a Ph.D. student in Computer Science at the Humanoid Robots Lab, under the supervision of Prof. Maren Bennewitz, at the University of Bonn, Germany. His research interests focus on active and interactive perception, viewpoint planning, and 3D reconstruction, particularly in tabletop and agricultural scenarios.
Presentation Abstract
Automating labor-intensive tasks such as crop monitoring with robots is essential for enhancing production and conserving resources. However, autonomously monitoring horticulture crops remains challenging due to their complex structures, which often result in fruit occlusions. Existing view planning methods attempt to reduce occlusions but either struggle to achieve adequate coverage or incur high robot motion costs. We introduce a global optimization approach for view motion planning that aims to minimize robot motion costs while maximizing fruit coverage. To this end, we leverage coverage constraints derived from the set covering problem within a shortest Hamiltonian path problem formulation. This integration enables a unified framework that computes a global view path with minimized motion while ensuring full coverage of selected targets. We demonstrate our system in a real-world setup and perform quantitative comparison in glasshouse simulation.
Co-Authors: Maren Bennewitz, Kris Hauser