The below figure shows a ground truth body trajectory (gt, black) and ground truth landmarks (lmk, blue). The goal is to run a SLAM simulation using NLS optimization as the backend and vision as the front end. A dead reckoning signal (dr, red) is generated using an IMU (with noise) and feature point...
The below figures show the ground truth (gt, black), a noisy dead reckoning signal (dr, red), and an NLS optimization using the noisy dr as a seed, and IMU data to constrain relative motion. The above figure shows all trajectories, and landmarks (lmk, navy) and feature points (plmk, green). ...
Yifei optimized algorithm as well as code this week and test it on our collected data, Under complicated environment with reflection and disturbance from other objects, the major part of green balls were found with contours as well as centers.
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