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Contribution Details
| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | Rethinking Trajectory Evaluation for SLAM: a Probabilistic, Continuous-Time Approach |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Event Title | ICRA19 Workshop on Dataset Generation and Benchmarking of SLAM Algorithms for Robotics and VR/AR |
| Event Type | workshop |
| Event Location | Montreal, Canada |
| Event Start Date | May 20 - 2019 |
| Event End Date | May 24 - 2019 |
| Place of Publication | IEEE |
| Publisher | arxiv |
| Abstract Text | Despite the existence of different error metrics for trajectory evaluation in SLAM, their theoretical justifications and connections are rarely studied, and few methods handle temporal association properly. In this work, we propose to formulate the trajectory evaluation problem in a probabilistic, continuous-time framework. By modeling the groundtruth as random variables, the concepts of absolute and relative error are generalized to be likelihood. Moreover, the groundtruth is represented as a piecewise Gaussian Process in continuous-time. Within this framework, we are able to establish theoretical connections between relative and absolute error metrics and handle temporal association in a principled manner. |
| Free access at | Official URL |
| Official URL | https://arxiv.org/abs/1906.03996 |
| Other Identification Number | merlin-id:20294 |
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