We recently released this video on autonomous exploration and inspection. Have a look!
The robot employs its visual-inertial navigation system in order to localize itself in the environment and simultaneously map it and 3D reconstruct it. Based on the newly proposed "Receding Horizon Next-Best-View Planner" the robot computes the next best step for efficient volumetric-exploration of unknown spaces. This is achieved by predicting a sequence of next-best-views via sampling-based methods and information gain approaches, executing only the first step and then repeating the whole process in a receding horizon fashion. Once full volumetric-exploration has been achieved, the robot starts focusing on the surface reconstruction of objects of interest in the environment.
A. Bircher, M. Kamel, K. Alexis, H. Oleynikova, R. Siegwart, "Receding Horizon "Next-Best-View" Planner for 3D Exploration", IEEE International Conference on Robotics and Automation 2016 (ICRA 2016), Stockholm, Sweden
The paper is accepted and will be presented at ICRA this year.
The code is to be open sourced and will be available once the paper is presented but also before. Send us an e-mail if you have interest already and we will update you once it is out.
Previous relevant work (but at the problem of optimized inspection while known a geometrical model of the structure):
A. Bircher, K. Alexis, M. Burri, P. Oettershagen, S. Omari, T. Mantel, R. Siegwart, "Structural Inspection Path Planning via Iterative Viewpoint Resampling with Application to Aerial Robotics", IEEE International Conference on Robotics & Automation, May 26-30, 2015 (ICRA 2015), Seattle, Washington, USA .
Hope you like it!