1 code implementation • 9 Oct 2024 • Rob Royce, Marcel Kaufmann, Jonathan Becktor, Sangwoo Moon, Kalind Carpenter, Kai Pak, Amanda Towler, Rohan Thakker, Shehryar Khattak
The advancement of robotic systems has revolutionized numerous industries, yet their operation often demands specialized technical knowledge, limiting accessibility for non-expert users.
no code implementations • 17 Sep 2024 • Manthan Patel, Jonas Frey, Deegan Atha, Patrick Spieler, Marco Hutter, Shehryar Khattak
RoadRunner M&M achieves a significant improvement of up to 50% for elevation mapping and 30% for traversability estimation over RoadRunner, and is able to predict in 30% more regions compared to X-Racer while achieving real-time performance.
no code implementations • 29 Feb 2024 • Jonas Frey, Manthan Patel, Deegan Atha, Julian Nubert, David Fan, Ali Agha, Curtis Padgett, Patrick Spieler, Marco Hutter, Shehryar Khattak
Furthermore, RoadRunner improves the system latency by a factor of roughly 4, from 500 ms to 140 ms, while improving the accuracy for traversability costs and elevation map predictions.
no code implementations • 30 Jan 2024 • Chanyoung Chung, Georgios Georgakis, Patrick Spieler, Curtis Padgett, Ali Agha, Shehryar Khattak
We experimentally validate the applicability of our proposed approach for autonomous offroad robotic navigation in complex and unstructured terrain using real-world offroad driving data.
no code implementations • 3 Jan 2023 • Shreyansh Daftry, Zhanlin Chen, Yang Cheng, Scott Tepsuporn, Brian Coltin, Ussama Naam, Lanssie Mingyue Ma, Shehryar Khattak, Matthew Deans, Larry Matthies
In previous work, we developed crater detection algorithms for three different sensing modalities.
no code implementations • 26 Oct 2022 • Manthan Patel, Gabriel Waibel, Shehryar Khattak, Marco Hutter
Detecting objects of interest, such as human survivors, safety equipment, and structure access points, is critical to any search-and-rescue operation.
1 code implementation • 11 Mar 2022 • Julian Nubert, Etienne Walther, Shehryar Khattak, Marco Hutter
LiDAR-based localization and mapping is one of the core components in many modern robotic systems due to the direct integration of range and geometry, allowing for precise motion estimation and generation of high quality maps in real-time.
1 code implementation • 10 Nov 2020 • Julian Nubert, Shehryar Khattak, Marco Hutter
Reliable robot pose estimation is a key building block of many robot autonomy pipelines, with LiDAR localization being an active research domain.
Robotics
no code implementations • 5 Mar 2019 • Shehryar Khattak, Christos Papachristos, Kostas Alexis
This paper proposes a method for tight fusion of visual, depth and inertial data in order to extend robotic capabilities for navigation in GPS-denied, poorly illuminated, and texture-less environments.
no code implementations • 5 Mar 2019 • Shehryar Khattak, Christos Papachristos, Kostas Alexis
Visible spectrum cameras are the most commonly used sensors due to their low cost and weight.
no code implementations • 3 Mar 2019 • Shehryar Khattak, Christos Papachristos, Kostas Alexis
This paper proposes an approach for fusing direct radiometric data from a thermal camera with inertial measurements to extend the robotic capabilities of aerial robots for navigation in GPS-denied and visually degraded environments in the conditions of darkness and in the presence of airborne obscurants such as dust, fog and smoke.
no code implementations • 2 Mar 2019 • Shehryar Khattak, Christos Papachristos, Kostas Alexis
For robotic inspection tasks in known environments fiducial markers provide a reliable and low-cost solution for robot localization.