Overlap-based ICP Tuning for Robust Localization of a Humanoid Robot

S. Nobili, R. Scona, M. Caravagna, M. Fallon

Research output: Chapter in Book/Report/Conference proceedingConference contribution


State estimation techniques for humanoid robots are typically based on proprioceptive sensing and accumulate drift over time. This drift can be corrected using exteroceptive sensors such as laser scanners via a scene registration procedure. For this procedure the common assumption of high point cloud overlap is violated when the scenario and the robot’s point-of-view are not static and the sensor’s field-of-view (FOV) is limited. In this paper we focus on the localization of a robot with limited FOV in a semi-structured environment. We analyze the effect of overlap variations on registration performance and demonstrate that where overlap varies, outlier filtering needs to be tuned accordingly. We define a novel parameter which gives a measure of this overlap. In this context, we propose a strategy for robust non-incremental registration. The pre-filtering module selects planar macro-features from the input clouds, discarding clutter. Outlier filtering is automatically tuned at run-time to allow registration to a common reference in conditions of non-uniform overlap. An extensive experimental demonstration is presented which characterizes the performance of the algorithm using two humanoids: the NASA Valkyrie, in a laboratory environment, and the Boston Dynamics Atlas, during the DARPA Robotics Challenge Finals.
Original languageEnglish
Title of host publication2017 IEEE International Conference on Robotics and Automation (ICRA)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Electronic)978-1-5090-4633-1
ISBN (Print)978-1-5090-4634-8
Publication statusPublished - 24 Jul 2017
Event2017 IEEE International Conference on Robotics and Automation - Singapore, Singapore
Duration: 29 May 20173 Jun 2017


Conference2017 IEEE International Conference on Robotics and Automation
Abbreviated titleICRA 2017
Internet address

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