Journal Article10.1109/LRA.2018.2795651
Complementary Perception for Handheld SLAM
Thomas Lowe,Soohwan Kim,Mark Cox +2 more
- 23 Jan 2018
- Vol. 3, Iss: 2, pp 1104-1111
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TL;DR: A key component of the proposed algorithm is the incorporation of depth uncertainty into visual features, which is effective for noisy surfaces and allows features with and without depth estimates to be modeled in a unified manner.
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Abstract: We present a novel method for mapping general three-dimensional environments, where sufficient geometric or visual information is not everywhere guaranteed and where the device motion is unconstrained as with handheld systems. The continuous-time simultaneous localization and mapping algorithm integrates a lidar, camera, and inertial measurement unit in a complementary fashion whereby all sensors contribute constraints to the optimization. The proposed algorithm is designed to expand the domain of mappable environments and therefore increase the reliability and utility of general purpose mobile mapping. A key component of the proposed algorithm is the incorporation of depth uncertainty into visual features, which is effective for noisy surfaces and allows features with and without depth estimates to be modeled in a unified manner. Results demonstrate a wider mappable domain on challenging environments compared to the state-of-the-art lidar or vision-based localization and mapping algorithms.
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Citations
Tightly Coupled 3D Lidar Inertial Odometry and Mapping
Haoyang Ye,Yuying Chen,Ming Liu +2 more
- 20 May 2019
TL;DR: The proposed tightly coupled lidar-IMU fusion method can estimate the poses of the sensor pair at the IMU update rate with high precision, even under fast motion conditions or with insufficient features.
543
UAV in the advent of the twenties: Where we stand and what is next
TL;DR: In this article , the authors review best practices for the use of UAVs for remote sensing and mapping applications and report on current trends -including adjacent domains - for UAV use and discuss their future impact in photogrammetry and remote sensing.
171
A Review of Multi-Sensor Fusion SLAM Systems Based on 3D LIDAR
TL;DR: The basic principles and recent work of multi-sensor fusion in detail are introduced in detail from four aspects based on the types of fused sensors and data coupling methods.
156
Complementary Multi–Modal Sensor Fusion for Resilient Robot Pose Estimation in Subterranean Environments
Shehryar Khattak,Huan X. Nguyen,Frank Mascarich,Tung Dang,Kostas Alexis +4 more
- 01 Sep 2020
TL;DR: A complementary multi–modal sensor fusion approach is presented that improves the reliability of the pose estimation process for aerial robots by fusing visual–inertial (VIO) and thermal–inERTial (TIO) odometry estimates with a LiDAR odometry and mapping solution.
145
Peer Review
UAV in the advent of the twenties: Where we stand and what is next
Francesco Nex,Costas Armenakis,Michael Cramer,Davide Antonio Cucci,M. Gerke,Eija Honkavaara,Antero Kukko,Claudio Persello,Jan Skaloud +8 more
TL;DR: In this paper , the authors review best practices for the use of UAVs for remote sensing and mapping applications and report on current trends for UAV use and discuss their future impact in photogrammetry and remote sensing.
123
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