Graph-based Multi-sensor Fusion for Consistent Localization of Autonomous Construction Robots (Talk)

Presentation for the IEEE International Conference on Robotics and Automation (ICRA) 2022 Julian Nubert, Shehryar Khattak and Marco Hutter Paper: Code: Abstract: Enabling autonomous operation of large-scale construction machines, such as excavators, can bring key benefits for human safety and operational opportunities for applications in dangerous and hazardous environments. To facilitate robot autonomy, robust and accurate state-estimation remains a core component to enable these machines for operation in a diverse set of complex environments. In this work, a method for multimodal sensor fusion for robot state-estimation and localization is presented, enabling operation of construction robots in realworld scenarios. The proposed approach presents a graph-based prediction-update loop that combines the benefits of filtering and smoothing in order to provide consistent state estimates at high update rate, while maintaining accurate