A method for evaluating, at video rate, the quality of actions for a single camera while mapping unknown indoor environments is presented. The strategy maximizes mutual information between measurements and states to help the camera avoid making ill-conditioned measurements that are appropriate to lack of depth in monocular vision systems. Our system prompts a user with the appropriate motion commands during 6-DOF visual simultaneous localization and mapping with a handheld camera. Additionally, the system has been ported to a mobile robotic platform, thus closing the control-estimation loop. To show the viability of the approach, simulations and experiments are presented for the unconstrained motion of a handheld camera and for the motion of a mobile robot with nonholonomic constraints. When combined with a path planner, the technique safely drives to a marked goal while, at the same time, producing an optimal estimated map. ; Postprint (published version)
Action selection for single-camera SLAM
2010-01-01
Article (Journal)
Electronic Resource
English
Classificació INSPEC::Pattern recognition::Computer vision::Active vision , Visió per ordinador , Path planning , Computer vision , bearing-only simultaneous localization and mapping (SLAM) , Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo , Active vision , Robots , Mutual information
DDC: | 629 |
ORB-SLAM based semi-dense mapping with monocular camera
IEEE | 2017
|Dynamic view selection for multi-camera action recognition
British Library Online Contents | 2016
|