This paper addresses the problem of real-time vision-based autonomous obstacle avoidance in unstructured environments for quadrotor UAVs. We assume that our UAV is equipped with a forward facing stereo camera as the only sensor to perceive the world around it. Moreover, all the computations are performed onboard. Feasible trajectory generation in this kind of problems requires rapid collision checks along with efficient planning algorithms. We propose a trajectory generation approach in the depth image space, which refers to the environment information as depicted by the depth images. In order to predict the collision in a look ahead robot trajectory, we create depth images from the sequence of robot poses along the path. We compare these images with the depth images of the actual world sensed through the forward facing stereo camera. We aim at generating fuel optimal trajectories inside the depth image space. In case of a predicted collision, a switching strategy is used to aggressively deviate the quadrotor away from the obstacle. For this purpose we use two closed loop motion primitives based on Linear Quadratic Regulator (LQR) objective functions. The proposed approach is validated through simulation and hardware experiments.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Real-time Quadrotor Navigation Through Planning in Depth Space in Unstructured Environments*


    Beteiligte:
    Ahmad, Shakeeb (Autor:in) / Fierro, Rafael (Autor:in)


    Erscheinungsdatum :

    01.06.2019


    Format / Umfang :

    596152 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Path planning in image space for autonomous robot navigation in unstructured environments

    Otte, M. W. / Richardson, S. G. / Mulligan, J. et al. | British Library Online Contents | 2009


    Real-time path planning of autonomous vehicles for unstructured road navigation

    Chu, K. / Kim, J. / Jo, K. et al. | Springer Verlag | 2015


    Real-time path planning of autonomous vehicles for unstructured road navigation

    Chu, K. / Kim, J. / Jo, K. et al. | Online Contents | 2015


    Real-time path planning of autonomous vehicles for unstructured road navigation

    Chu, K. / Kim, J. / Jo, K. et al. | British Library Online Contents | 2015


    Vehicle Planning in Unstructured Environments

    Green, Alexander / Rye, David / Durrant-Whyte, Hugh | AIAA | 2005