This paper presents a new model-based egomotion estimation algorithm for an autonomous vehicle navigating through rough terrain. Due to the uneven terrain, the vehicle undergoes bouncing, pitch and roll motion. To reliably accomplish other tasks such as tracking and obstacle avoidance using visual inputs, it is essential to consider these disturbances. In this paper, two vehicle models available in the literature are used for egomotion estimation. The Half Vehicle Model (HVM) takes into account the bouncing and pitch motion of the vehicle, and the Full Vehicle Model (FVM) also considers the roll motion. The dynamics of the vehicle are formulated using standard equations of motion. Assuming that depth information is known for some landmarks in the scene (e.g., obtained from a laser range finder), a feature-based approach is proposed to estimate vehicle motion parameters such as the vertical movement of the center of mass and the instantaneous angular velocity. An Iterated Extended Kalman Filter (IEKF) is used for recursive parameter estimation. Simulation results for both known and unknown terrain are presented. Motion estimation, Navigation, Vehicle dynamics.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    Estimation of Vehicle Dynamics from Monocular Noisy Images


    Contributors:
    Y. S. Yao (author) / R. Chellappa (author)

    Publication date :

    1993


    Size :

    22 pages


    Type of media :

    Report


    Type of material :

    No indication


    Language :

    English




    Estimation of motion and structure from monocular images

    Shioyama,T. / Yamauchi,H. / Kyoto Inst.of Technol.,JP | Automotive engineering | 1993



    Lightweight and Effective Convolutional Neural Networks for Vehicle Viewpoint Estimation From Monocular Images

    Magistri, Simone / Boschi, Marco / Sambo, Francesco et al. | BASE | 2022

    Free access

    93ME085 Estimation of Motion and Structure from Monocular Images

    Shioyama, T. / Yamauchi, H. / ISATA et al. | British Library Conference Proceedings | 1993