In this paper we propose a framework for trajectory planning and control of tracked vehicles for rescue environments, based on Augmented Reality (AR). The framework provides the human operator with an AR-based interface that facilitates both 3D path planning and obstacle negotiation. The interface converts the 3D movements of a marker pen, handheld by the operator, into trajectories feasible for the tracked vehicle. The framework implements a trajectory tracking controller to allow the tracked vehicle to autonomously follow the trajectories, decided by the operator. This controller relies on a localization system which provides, at real-time, position feedback. The localization system exploits the performance of a Dead Reckoning System together with the accuracy of an ICP-based SLAM in pose estimation, to determine the pose of the tracked vehicle within the 3D map. We demonstrate the application of the planning framework in autonomous robot navigation for evaluating the robot capabilities in rescue environments. Our experiments show the effectiveness of the trajectory tracking control method. © 2013 IEEE.
An Augmented Reality approach for trajectory planning and control of tracked vehicles in rescue environments / Gianni, Mario; Gianpaolo, Gonnelli; Sinha, Arnab; Menna, Matteo; PIRRI ARDIZZONE, Maria Fiora. - ELETTRONICO. - (2013), pp. 1-6. (Intervento presentato al convegno 2013 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2013 tenutosi a Linkoping, Sweden nel 21 October 2013 through 26 October 2013) [10.1109/ssrr.2013.6719360].
An Augmented Reality approach for trajectory planning and control of tracked vehicles in rescue environments
GIANNI, Mario;SINHA, ARNAB;MENNA, MATTEO;PIRRI ARDIZZONE, Maria Fiora
2013
Abstract
In this paper we propose a framework for trajectory planning and control of tracked vehicles for rescue environments, based on Augmented Reality (AR). The framework provides the human operator with an AR-based interface that facilitates both 3D path planning and obstacle negotiation. The interface converts the 3D movements of a marker pen, handheld by the operator, into trajectories feasible for the tracked vehicle. The framework implements a trajectory tracking controller to allow the tracked vehicle to autonomously follow the trajectories, decided by the operator. This controller relies on a localization system which provides, at real-time, position feedback. The localization system exploits the performance of a Dead Reckoning System together with the accuracy of an ICP-based SLAM in pose estimation, to determine the pose of the tracked vehicle within the 3D map. We demonstrate the application of the planning framework in autonomous robot navigation for evaluating the robot capabilities in rescue environments. Our experiments show the effectiveness of the trajectory tracking control method. © 2013 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.