Dataset 1: Star shaped trajectory optimization using manhattan constraints

README.md

1. Following are the results of noisy star shaped trajectory optimization just using manhattan constraints.

1. Dense ground truth trajectory:
   

2. Dense noisy trajectory:
   

3. Manhattan sparse trajectory:
   

4. Transformation of all the nodes with respect to the first node in above manhattan trajectory is caculated and given as loop closing constraints. It can be seen as overlying 3rd image constraints over 2nd image dense noisy trajectory.
   Before g2o optimiztion:
   

5. After g2o optmization:
   

6. There is rotation effect in the optimized trajectory, as the starting node in noisy trajectory itself is rotated from ground truth starting node and that node is fixed in optimization.