266 citations · 407 across the 12 of their papers we have counts for
17 papers · 1 filter
Brace Yourself: Task-Conditioned Environmental Bracing for Forceful Humanoid Manipulation
Zongyuan Zhang, Christopher Lehnert, Will N. Browne +1
Forceful manipulation is challenging for humanoid robots because interaction forces can disturb whole-body balance. We introduce the Supporting Hand Strategy (SHS), which enables a…
Reactive Base Control for On-The-Move Mobile Manipulation in Dynamic Environments
Ben Burgess-Limerick, Jesse Haviland, Chris Lehnert +1
We present a reactive base control method that enables high performance mobile manipulation on-the-move in environments with static and dynamic obstacles. Performing manipulation t…
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-…
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…
Combining Local and Global Viewpoint Planning for Fruit Coverage
Tobias Zaenker, Chris Lehnert, Chris McCool +1
Obtaining 3D sensor data of complete plants or plant parts (e.g., the crop or fruit) is difficult due to their complex structure and a high degree of occlusion. However, especially…
Towards Active Robotic Vision in Agriculture: A Deep Learning Approach to Visual Servoing in Occluded and Unstructured Protected Cropping Environments
Paul Zapotezny-Anderson, Chris Lehnert
3D Move To See (3DMTS) is a mutli-perspective visual servoing method for unstructured and occluded environments, like that encountered in robotic crop harvesting. This paper presen…