129 citations · 248 across the 11 of their papers we have counts for
12 papers
Graph-Based Design of Soft Grippers with Multi-Objective Quality-Diversity Optimisation
Andre Farinha, Ge Shi, Harry Bowman +3
Effective manipulation across diverse objects is critical for applications ranging from agricultural harvesting to laboratory and domestic automation. While the inherent compliance…
Alternative Interfaces for Human-initiated Natural Language Communication and Robot-initiated Haptic Feedback: Towards Better Situational Awareness in Human-Robot Collaboration
Callum Bennie, Bridget Casey, Cecile Paris +9
This article presents an implementation of a natural-language speech interface and a haptic feedback interface that enables a human supervisor to provide guidance to, request infor…
Robotic Vision for Human-Robot Interaction and Collaboration: A Survey and Systematic Review
Nicole Robinson, Brendan Tidd, Dylan Campbell +2
Robotic vision for human-robot interaction and collaboration is a critical process for robots to collect and interpret detailed information related to human actions, goals, and pre…
Learning Visuo-Motor Behaviours for Robot Locomotion Over Difficult Terrain
Brendan Tidd
As mobile robots become useful performing everyday tasks in complex real-world environments, they must be able to traverse a range of difficult terrain types such as stairs, steppi…
Heterogeneous robot teams with unified perception and autonomy: How Team CSIRO Data61 tied for the top score at the DARPA Subterranean Challenge
Navinda Kottege, Jason Williams, Brendan Tidd +27
The DARPA Subterranean Challenge was designed for competitors to develop and deploy teams of autonomous robots to explore difficult unknown underground environments. Categorised in…
Human-Robot Team Performance Compared to Full Robot Autonomy in 16 Real-World Search and Rescue Missions: Adaptation of the DARPA Subterranean Challenge
Nicole Robinson, Jason Williams, David Howard +6
Human operators in human-robot teams are commonly perceived to be critical for mission success. To explore the direct and perceived impact of operator input on task success and tea…
Residual Skill Policies: Learning an Adaptable Skill-based Action Space for Reinforcement Learning for Robotics
Krishan Rana, Ming Xu, Brendan Tidd +2
Skill-based reinforcement learning (RL) has emerged as a promising strategy to leverage prior knowledge for accelerated robot learning. Skills are typically extracted from expert d…
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…
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…
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…