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This paper presents a novel application of the Visual Servoing Platform’s (ViSP) for pose estimation in indoor and GPS-denied\udoutdoor environments. Our proposed solution integrates the trajectory solution from RGBD-SLAM into ViSP’s pose estimation\udprocess. Li-Chee-Ming and Armenakis (2015) explored the application of ViSP in mapping large outdoor environments, and tracking\udlarger objects (i.e., building models). Their experiments revealed that tracking was often lost due to a lack of model features in the\udcamera’s field of view, and also because of rapid camera motion. Further, the pose estimate was often biased due to incorrect feature\udmatches. This work proposes a solution to improve ViSP’s pose estimation performance, aiming specifically to reduce the frequency\udof tracking losses and reduce the biases present in the pose estimate. This paper explores the integration of ViSP with RGB-D\udSLAM. We discuss the performance of the combined tracker in mapping indoor environments and tracking 3D wireframe indoor\udbuilding models, and present preliminary results from our experiments

the international archives of the photogrammetry, remote sensing and spatial information sciences/international archives of the photogrammetry, remote sensing and spatial information sciences

Augmenting ViSP’s 3D Model-Based Tracker with RGB-D SLAM for 3D Pose Estimation in Indoor Environments