211 citations · 432 across the 31 of their papers we have counts for
4 papers · 1 filter
An Architecture for Reactive Mobile Manipulation On-The-Move
Ben Burgess-Limerick, Chris Lehnert, Jurgen Leitner +1
We present a generalised architecture for reactive mobile manipulation while a robot's base is in motion toward the next objective in a high-level task. By performing tasks on-the-…
Deep Learning Approaches to Grasp Synthesis: A Review
Rhys Newbury, Morris Gu, Lachlan Chumbley +9
Grasping is the process of picking up an object by applying forces and torques at a set of contacts. Recent advances in deep-learning methods have allowed rapid progress in robotic…
Integrating High-Resolution Tactile Sensing into Grasp Stability Prediction
Lachlan Chumbley, Morris Gu, Rhys Newbury +2
We investigate how high-resolution tactile sensors can be utilized in combination with vision and depth sensing, to improve grasp stability prediction. Recent advances in simulatin…
DGBench: An Open-Source, Reproducible Benchmark for Dynamic Grasping
Ben Burgess-Limerick, Chris Lehnert, Jurgen Leitner +1
This paper introduces DGBench, a fully reproducible open-source testing system to enable benchmarking of dynamic grasping in environments with unpredictable relative motion between…