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Robotic systems need advanced mobility capabilities to operate in complex,three-dimensional environments designed for human use, e.g., multi-levelbuildings. Incorporating some level of autonomy enables robots to operaterobustly, reliably, and efficiently in such complex environments, e.g.,automatically "returning home" if communication between an operator and robotis lost during deployment. This work presents a novel method that enablesmobile robots to robustly operate in multi-level environments by making itpossible to autonomously locate and climb a range of different staircases. Wepresent results wherein a wheeled robot works together with a quadrupedalsystem to quickly detect different staircases and reliably climb them. Theperformance of this novel staircase detection algorithm that is able to run onthe heterogeneous platforms is compared to the current state-of-the-artdetection algorithm. We show that our approach significantly increases theaccuracy and speed at which detections occur.

Fast Staircase Detection and Estimation using 3D Point Clouds with Multi-detection Merging for Heterogeneous Robots