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PhD Speaking Qualifier


Paloma Sodhi PhD Student Robotics Institute,
Carnegie Mellon University
November 14, 2019
9:30 am
- 10:30 am
GHC 4405
Online and Consistent Occupancy Grid Mapping

Actively exploring and mapping an unknown environment requires integration of both simultaneous localization and mapping (SLAM) and path planning methods. Path planning relies on a map that contains free and occupied space information and is efficient to query, while the role of SLAM is to keep the map consistent as new measurements are continuously added. A key challenge lies in ensuring a map representation compatible with both these objectives: that is, a map that maintains free space information for planning but can also adapt efficiently to dynamically changing pose estimates from a graph-based SLAM system.

In this talk, I will discuss methods ranging from purely local to global occupancy mapping. We present an online mapping approach that can be corrected for accumulated drift efficiently based on incremental solutions from a sparse graph-based SLAM optimization. We’ll demonstrate use of such a representation for implementing an underwater SLAM system in which the robot actively plans paths to generate accurate 3D scene reconstructions. We evaluate performance for both simulated and real-world datasets.

Michael Kaess (advisor)
David Wettergreen
Martial Hebert
Kumar Shaurya Shankar