1 citations · 1 across the 6 of their papers we have counts for
6 papers
A Real-World Grasping-in-Clutter Performance Evaluation Benchmark for Robotic Food Waste Sorting
Moniesha Thilakarathna, Xing Wang, Min Wang +3
Food waste management is critical for sustainability, yet inorganic contaminants hinder recycling potential. Robotic automation accelerates sorting through automated contaminant re…
The Morphology-Control Trade-Off: Insights into Soft Robotic Efficiency
Yue Xie, Kai-fung Chu, Xing Wang +1
Soft robotics holds transformative potential for enabling adaptive and adaptable systems in dynamic environments. However, the interplay between morphological and control complexit…
SoGraB: A Visual Method for Soft Grasping Benchmarking and Evaluation
Benjamin G. Greenland, Josh Pinskier, Xing Wang +5
Recent years have seen soft robotic grippers gain increasing attention due to their ability to robustly grasp soft and fragile objects. However, a commonly available standardised e…
DexGrip: Multi-modal Soft Gripper with Dexterous Grasping and In-hand Manipulation Capacity
Xing Wang, Liam Horrigan, Josh Pinskier +6
The ability of robotic grippers to not only grasp but also re-position and re-orient objects in-hand is crucial for achieving versatile, general-purpose manipulation. While recent…
PINN-Ray: A Physics-Informed Neural Network to Model Soft Robotic Fin Ray Fingers
Xing Wang, Joel Janek Dabrowski, Josh Pinskier +4
Modelling complex deformation for soft robotics provides a guideline to understand their behaviour, leading to safe interaction with the environment. However, building a surrogate…
Fin-QD: A Computational Design Framework for Soft Grippers: Integrating MAP-Elites and High-fidelity FEM
Yue Xie, Xing Wang, Fumiya Iida +1
Computational design can excite the full potential of soft robotics that has the drawbacks of being highly nonlinear from material, structure, and contact. Up to date, enthusiastic…