Lifan Luo — accepted AI-conference papers

2025

Master Rules from Chaos: Learning to Reason, Plan, and Interact from Chaos for Tangram Assembly

Chao Zhao, Chunli Jiang, Lifan Luo, Guanlan Zhang, Hongyu Yu, Michael Yu Wang +1

ICRA 2025

Tangram assembly, the art of human intelligence and manipulation dexterity, is a new challenge for robotics and reveals the limitations of state-of-the-arts. Here, we describe our initial exploration and highlight key problems in reasoning, planning, and manipulation for robotic tangram assembly. We

Cited by 1 Source ↗code ↗Scholar ↗

2024

CompdVision: Combining Near-Field 3D Visual and Tactile Sensing Using a Compact Compound-Eye Imaging System

Lifan Luo, Boyang Zhang, Zhijie Peng, Yik Kin Cheung, Guanlan Zhang, Zhigang Li +2

IROS 2024poster

As automation technologies advance, the need for compact and multi-modal sensors in robotic applications is growing. To address this demand, we introduce CompdVision, a novel sensor that employs a compound-eye imaging system to combine near-field 3D visual and tactile sensing within a compact form f…

Cited by 1 Source ↗Scholar ↗