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About Learning To Calibrate: Reinforcement Learning For Guided Calibration of Visual-Inertial Rigs
1. The document presents a new approach to visual-inertial calibration that uses reinforcement learning to guide users through the calibration process by suggesting motions that make calibration parameters observable. 2. It models calibration as a Markov decision process and uses reinforcement learning to determine the sequence of motions that best estimates calibration parameters. 3. The goal is to address the common assumption that calibration routines require sufficiently exciting motions, and make calibration accessible to non-experts by automating motion guidance.
Detailed Information
| Author: | ['riyanto riyanto'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 15 |
| Language: | English |
| Format: | |
| Price: | FREE |
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