EARLIEST PROJECT START FALL 2019! We have recently developed decentralized multi-robot visual place recognition (neural network based) and SLAM and demonstrated them on well-known datasets ( http://rpg.ifi.uzh.ch/docs/arXiv17_Cieslewski.pdf ). We want to take this work one step further and deploy it in the real world with a group of quadrotors. Since this is quite an effort, logistically, a first step will be to simulate the full system (SLAM, but also obstacle avoidance and control) in simulation.
EARLIEST PROJECT START FALL 2019! We have recently developed decentralized multi-robot visual place recognition (neural network based) and SLAM and demonstrated them on well-known datasets ( http://rpg.ifi.uzh.ch/docs/arXiv17_Cieslewski.pdf ). We want to take this work one step further and deploy it in the real world with a group of quadrotors. Since this is quite an effort, logistically, a first step will be to simulate the full system (SLAM, but also obstacle avoidance and control) in simulation.
In this project, you will simulate a scenario where a group of quadrotors explores and maps an unknown environment. We will start with a simplistic simulation and gradually increase its complexity. Axes in which to complexity can be increased: From manual camera placement to using a full control stack, from rendering camera frames in Gazebo to rendering them in a more photorealistic simulator, from random motion with reactive obstacle avoidance to active exploration, from a few robots to many robots, …
In this project, you will simulate a scenario where a group of quadrotors explores and maps an unknown environment. We will start with a simplistic simulation and gradually increase its complexity. Axes in which to complexity can be increased: From manual camera placement to using a full control stack, from rendering camera frames in Gazebo to rendering them in a more photorealistic simulator, from random motion with reactive obstacle avoidance to active exploration, from a few robots to many robots, …
Titus Cieslewski ( titus at ifi.uzh.ch ), ATTACH CV AND TRANSCRIPT! Required skills: Linux, experience in ROS or a very strong ability to learn, C++/Python.
Titus Cieslewski ( titus at ifi.uzh.ch ), ATTACH CV AND TRANSCRIPT! Required skills: Linux, experience in ROS or a very strong ability to learn, C++/Python.