Picking the raisins out of the cookie LiDAR based odometry in dynamic urban environments
dc.contributor.author | Åberg, Andreas | |
dc.contributor.department | Chalmers tekniska högskola / Institutionen för elektroteknik | sv |
dc.contributor.examiner | Hammarstrand, Lars | |
dc.contributor.supervisor | Hammarstrand, Lars | |
dc.contributor.supervisor | Lozano Calvo, Ernesto | |
dc.date.accessioned | 2025-07-04T13:54:47Z | |
dc.date.issued | 2025 | |
dc.date.submitted | ||
dc.description.abstract | Reliable localization using LiDAR on pedestrian-scale delivery robots in urban environments poses distinctive challenges. Methods proven on larger vehicles with high-end sensors do not necessarily translate to compact platforms with simpler payloads. This thesis focuses on evaluating some state-of-the-art LiDAR odometry approaches on a small delivery robot equipped with a LiDAR and other sensors such as an IMU. By comparing trajectory accuracy, resilience to real-world motion profiles, and multiple sensor configurations, insight is provided into which techniques can serve as a reliable baseline and what additional capabilities are required to achieve practical localization on often more resource-constrained robots. Building on this foundation, we explore targeted enhancements driven by real-world observations. We implement a real-time simple dynamic-object filtering approach that operates in parallel with odometry, based on a range images, where moving objects are subsequently identified and excised to maintain a static map. To further mitigate drift over extended runs, we integrate loop-closure adjustments, detecting and aligning previously visited areas to correct accumulated drift over larger distances. Together, these refinements demonstrate how a robust baseline can be augmented to meet the demands of odometry and mapping of a small delivery robot. | |
dc.identifier.coursecode | EENX30 | |
dc.identifier.uri | http://hdl.handle.net/20.500.12380/309993 | |
dc.language.iso | eng | |
dc.setspec.uppsok | Technology | |
dc.subject | LiDAR Odometry | |
dc.subject | Urban Localization | |
dc.subject | Dynamic Object Removal | |
dc.subject | SLAM | |
dc.title | Picking the raisins out of the cookie LiDAR based odometry in dynamic urban environments | |
dc.type.degree | Examensarbete för masterexamen | sv |
dc.type.degree | Master's Thesis | en |
dc.type.uppsok | H | |
local.programme | Systems, control and mechatronics (MPSYS), MSc |