Register now After registration you will be able to apply for this opportunity online.
This opportunity is not published. No applications will be accepted.
Robust 3D exploration
Explore an unknown space in 3D, relying only on visual-inertial odometry (with drift) and basic place recognition (but no loop closure/map optimization).
Keywords: exploration SLAM VIO VO odometry
In exploration, a robot creates a map of a previously unknown environment. Typically, the goal is to cover all of the reachable space. Think of a robot deployed in a disaster area, tasked with finding all survivors (search and rescue). The problem with most current exploration algorithms is that they assume perfect pose estimates. The problem is that robots equipped with on-board pose estimators will always produce an estimate with an error/drift. In this project, you will work on achieving exploration not with a perfect, but rather realistic pose estimate.
In exploration, a robot creates a map of a previously unknown environment. Typically, the goal is to cover all of the reachable space. Think of a robot deployed in a disaster area, tasked with finding all survivors (search and rescue). The problem with most current exploration algorithms is that they assume perfect pose estimates. The problem is that robots equipped with on-board pose estimators will always produce an estimate with an error/drift. In this project, you will work on achieving exploration not with a perfect, but rather realistic pose estimate.
Explore an unknown space in 3D, relying only on visual-inertial odometry (with drift) and basic place recognition (but no loop closure/map optimization). Start in simulation, then possibly deploy in the real world (quad equipped with depth sensor).
Explore an unknown space in 3D, relying only on visual-inertial odometry (with drift) and basic place recognition (but no loop closure/map optimization). Start in simulation, then possibly deploy in the real world (quad equipped with depth sensor).
Titus Cieslewski ( titus at ifi.uzh.ch ), ATTACH CV AND TRANSCRIPT (also Bachelor)! Required skills: Linux, ROS. Ideally C++ and Python, but if you know only one you should also be fine.
Titus Cieslewski ( titus at ifi.uzh.ch ), ATTACH CV AND TRANSCRIPT (also Bachelor)! Required skills: Linux, ROS. Ideally C++ and Python, but if you know only one you should also be fine.