266 citations · 396 across the 7 of their papers we have counts for
11 papers
Developing cooperative policies for multi-stage reinforcement learning tasks
Jordan Erskine, Chris Lehnert
Many hierarchical reinforcement learning algorithms utilise a series of independent skills as a basis to solve tasks at a higher level of reasoning. These algorithms don't consider…
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…
Developing cooperative policies for multi-stage tasks
Jordan Erskine, Chris Lehnert
This paper proposes the Cooperative Soft Actor Critic (CSAC) method of enabling consecutive reinforcement learning agents to cooperatively solve a long time horizon multi-stage tas…
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…
A Sweet Pepper Harvesting Robot for Protected Cropping Environments
Chris Lehnert, Chris McCool, Inkyu Sa +1
Using robots to harvest sweet peppers in protected cropping environments has remained unsolved despite considerable effort by the research community over several decades. In this p…
3D Move to See: Multi-perspective visual servoing for improving object views with semantic segmentation
Chris Lehnert, Dorian Tsai, Anders Eriksson +1
In this paper, we present a new approach to visual servoing for robotics, referred to as 3D Move to See (3DMTS), based on the principle of finding the next best view using a 3D cam…