Towards Robust Localization and Mapping in Challenging Conditions (Note:1 PDH (Professional Development Hour) will be provided for Professional Engineers(PEs) upon the request)
At the core of most autonomous systems is a source of navigation data that provides position and orientation which often depends on a single state estimation system. This single-point of failure reduces robustness and reliability. Prior work in SLAM often focusses on accuracy. In this talk we will explore several ideas to improve the robustness of SLAM systems while maintaining high accuracy and mapping resolution. We present the challenges, as well as results of operating in dust, fog, high-resolution mapping, and robust place recognition in a variety of situations with traditional as well as learning-based approaches to SLAM.
Date and Time
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- Date: 28 Oct 2021
- Time: 05:30 PM to 06:45 PM
- All times are (UTC-06:00) Central Time (US & Canada)
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- Lincoln, Nebraska
- United States
- Starts 06 August 2021 12:00 AM
- Ends 28 October 2021 05:15 PM
- All times are (UTC-06:00) Central Time (US & Canada)
- No Admission Charge
Speakers
Dr. Sebastian Scherer
Towards Robust Localization and Mapping in Challenging Conditions
Biography:
Dr. Sebastian Scherer is an Associate Research Professor at the Robotics Institute (RI) at Carnegie Mellon University (CMU). His research focuses on enabling autonomy for unmanned rotorcraft to operate at low altitude in cluttered environments. He and His team have shown the fastest and most tested obstacle avoidance on an Yamaha RMax (2006), the first obstacle avoidance for micro aerial vehicles in natural environments (2008), and the first (2010) and fastest (2014) automatic landing zone detection and landing on a full-size helicopter. Dr. Scherer received his B.S. in Computer Science, M.S. and Ph.D. in Robotics from CMU in 2004, 2007, and 2010. He is a Siebel scholar and a recipient of multiple paper awards and nominations, including AIAA@Infotech 2010 and FSR 2013. His research has been covered by the national and internal press including IEEE Spectrum, the New Scientist, Wired, der Spiegel, and the WSJ. His work on self-landing helicopters has received the Popular Science Best of What's New 2010 Award. He currently leads CMU's entry into the DARPA SubT Challenge.