Online Behaviour Tree Synthesis for Adaptive Multi-Agent Coordination

Project Member(s): Best, G.

Funding or Partner Organisation: Google LLC
Google LLC

Start year: 2023

Summary: We have an expanding research program that aims to improve the usability of behaviour trees via three inter-related threads: (1) automatic synthesis of behaviour tree structures, (2) algorithm development to address specific challenges of multi-agent coordination, and (3) demonstrate their use on physical multi-robot systems in important application domains. This proposal outlines our current research in this field and a pathway for future work

Publications:

Davis, BR, Bray, E & Best, G 1970, 'Multi-Goal Path Planning in Cluttered Environments with PRM-Guided Self-Organising Maps', 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, Abu Dhabi, UAE, pp. 10746-10753.
View/Download from: Publisher's site

FOR Codes: Robotics, Field robotics

Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.