106 citations · 200 across the 9 of their papers we have counts for
9 papers
Heterogeneous Ground and Air Platforms, Homogeneous Sensing: Team CSIRO Data61's Approach to the DARPA Subterranean Challenge
Nicolas Hudson, Fletcher Talbot, Mark Cox +31
Heterogeneous teams of robots, leveraging a balance between autonomy and human interaction, bring powerful capabilities to the problem of exploring dangerous, unstructured subterra…
Passing Through Narrow Gaps with Deep Reinforcement Learning
Brendan Tidd, Akansel Cosgun, Jurgen Leitner +1
The U.S. Defense Advanced Research Projects Agency (DARPA) Subterranean Challenge requires teams of robots to traverse difficult and diverse underground environments. Traversing sm…
Learning Setup Policies: Reliable Transition Between Locomotion Behaviours
Brendan Tidd, Nicolas Hudson, Akansel Cosgun +1
Dynamic platforms that operate over many unique terrain conditions typically require many behaviours. To transition safely, there must be an overlap of states between adjacent cont…
Semi-supervised Gated Recurrent Neural Networks for Robotic Terrain Classification
Ahmadreza Ahmadi, Tønnes Nygaard, Navinda Kottege +2
Legged robots are popular candidates for missions in challenging terrains due to the wide variety of locomotion strategies they can employ. Terrain classification is a key enabling…
Bruce -- Design and Development of a Dynamic Hexapod Robot
Ryan Steindl, Thomas Molnar, Fletcher Talbot +4
This paper introduces Bruce, the CSIRO Dynamic Hexapod Robot capable of autonomous, dynamic locomotion over difficult terrain. This robot is built around Apptronik linear series el…
Learning When to Switch: Composing Controllers to Traverse a Sequence of Terrain Artifacts
Brendan Tidd, Nicolas Hudson, Akansel Cosgun +1
Legged robots often use separate control policiesthat are highly engineered for traversing difficult terrain suchas stairs, gaps, and steps, where switching between policies isonly…
Virtual Surfaces and Attitude Aware Planning and Behaviours for Negative Obstacle Navigation
Thomas Hines, Kazys Stepanas, Fletcher Talbot +5
This paper presents an autonomous navigation system for ground robots traversing aggressive unstructured terrain through a cohesive arrangement of mapping, deliberative planning an…
Guided Curriculum Learning for Walking Over Complex Terrain
Brendan Tidd, Nicolas Hudson, Akansel Cosgun
Reliable bipedal walking over complex terrain is a challenging problem, using a curriculum can help learning. Curriculum learning is the idea of starting with an achievable version…
Deep Leaf Segmentation Using Synthetic Data
Daniel Ward, Peyman Moghadam, Nicolas Hudson
Automated segmentation of individual leaves of a plant in an image is a prerequisite to measure more complex phenotypic traits in high-throughput phenotyping. Applying state-of-the…