Dynamic Obstacle Tracking
For his internship at Fetch Robotics during the winter of 2015/2016, Andrew Vaziri worked on a new costmap layer for better robot navigation in dynamic environments. His intern video describes how the costmap layer tracks dynamic obstacles, especially other robots. Using data from the laser range finder, robots are detected using a machine learning algorithm called “Random Forests”. Each potential robot instance is then tracked using a filter which can aggregate the data across several laser range finder scans.
We have finally caught up with editing, so check back soon to see even more intern videos over the next couple of weeks.