6 citations · 7 across the 2 of their papers we have counts for
3 papers
cs.RO2020★ 6 cited
Multi-Fingered Active Grasp Learning
Qingkai Lu, Mark Van der Merwe, Tucker Hermans
Learning-based approaches to grasp planning are preferred over analytical methods due to their ability to better generalize to new, partially observed objects. However, data collec…
cs.RO2019
Learning Continuous 3D Reconstructions for Geometrically Aware Grasping
Mark Van der Merwe, Qingkai Lu, Balakumar Sundaralingam +2
Deep learning has enabled remarkable improvements in grasp synthesis for previously unseen objects from partial object views. However, existing approaches lack the ability to expli…
cs.RO2019★ 1 cited
Modeling Grasp Type Improves Learning-Based Grasp Planning
Qingkai Lu, Tucker Hermans
Different manipulation tasks require different types of grasps. For example, holding a heavy tool like a hammer requires a multi-fingered power grasp offering stability, while hold…