425 citations · 539 across the 6 of their papers we have counts for
6 papers
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…
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…
PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learning
Guillaume Sartoretti, Justin Kerr, Yunfei Shi +4
Multi-agent path finding (MAPF) is an essential component of many large-scale, real-world robot deployments, from aerial swarms to warehouse automation. However, despite the commun…
Multi-Agent Path Finding with Deadlines
Hang Ma, Glenn Wagner, Ariel Felner +3
We formalize Multi-Agent Path Finding with Deadlines (MAPF-DL). The objective is to maximize the number of agents that can reach their given goal vertices from their given start ve…
Multi-Agent Path Finding with Deadlines: Preliminary Results
Hang Ma, Glenn Wagner, Ariel Felner +3
We formalize the problem of multi-agent path finding with deadlines (MAPF-DL). The objective is to maximize the number of agents that can reach their given goal vertices from their…
Rapid Randomized Restarts for Multi-Agent Path Finding Solvers
Liron Cohen, Glenn Wagner, T. K. Satish Kumar +2
Multi-Agent Path Finding (MAPF) is an NP-hard problem well studied in artificial intelligence and robotics. It has many real-world applications for which existing MAPF solvers use…