150 research outputs found
Efficient Visual Odometry and Mapping for Unmanned Aerial Vehicle Using ARM-based Stereo Vision Pre-Processing System
Visual odometry and mapping methods can provide accurate navigation and comprehensive environment (obstacle) information for autonomous flights of Unmanned Aerial Vehicle (UAV) in GPS-denied cluttered environments. This work presents a new light small-scale low-cost ARM-based stereo vision pre-processing system, which not only is used as onboard sensor to continuously estimate 6-DOF UAV pose, but also as onboard assistant computer to pre-process visual information, thereby saving more computational capability for the onboard host computer of the UAV to conduct other tasks. The visual odometry is done by one plugin specifically developed for this new system with a fixed baseline (12cm). In addition, the preprocessed infromation from this new system are sent via a Gigabit Ethernet cable to the onboard host computer of UAV for real-time environment reconstruction and obstacle detection with a octree-based 3D occupancy grid mapping approach, i.e. OctoMap. The visual algorithm is evaluated with the stereo video datasets from EuRoC Challenge III in terms of efficiency, accuracy and robustness. Finally, the new system is mounted and tested on a real quadrotor UAV to carry out the visual odometry and mapping task
Predictive Visual Tracking: A New Benchmark and Baseline Approach
As a crucial robotic perception capability, visual tracking has been
intensively studied recently. In the real-world scenarios, the onboard
processing time of the image streams inevitably leads to a discrepancy between
the tracking results and the real-world states. However, existing visual
tracking benchmarks commonly run the trackers offline and ignore such latency
in the evaluation. In this work, we aim to deal with a more realistic problem
of latency-aware tracking. The state-of-the-art trackers are evaluated in the
aerial scenarios with new metrics jointly assessing the tracking accuracy and
efficiency. Moreover, a new predictive visual tracking baseline is developed to
compensate for the latency stemming from the onboard computation. Our
latency-aware benchmark can provide a more realistic evaluation of the trackers
for the robotic applications. Besides, exhaustive experiments have proven the
effectiveness of the proposed predictive visual tracking baseline approach.Comment: 7 pages, 5 figure
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