Liang Han’s scientific contributions

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Publications (1)

Fig. 1. A quadrotor is flying on a projected AR scenario, using IPT to collect position data. Requiring no additional equipment, the quadrotor obtains pose from only projected images through a downward camera.
Fig. 3. The encoding process of binary pixels. Bit 0 and bit 1 are encoded as 60 FPS flashing in different phases. Since the flicker-fusion property, human eyes are difficult to perceive this high-speed lightness change.
Fig. 5. Intermediate steps present the process of extracting fiducial tags from a raw image Fig. (a). First, the tags appear in Fig. (b) after the subtraction of two successive frames. Then, the disturbances such as text and lines are eliminated by image alignment, as shown in Fig. (c). Next, Fig. (d) displays the preprocessing result. Each tag forms a continuous boundary, ensuring the success of tag detection in Fig. (e). Although the shadow affects the tag detection in the left-down corner, other tags are still detected successfully. This shadow-tolerant character verifies the configuration of the tag map.
Fig. 6. IPT AR flight system, adding UWB and OptiTrack for comparison. The UWB system includes one tag on the quadrotor and four base anchors. OptiTrack uses a dozen of cameras to provide submillimeter-level position.
Indoor Localization for Quadrotors using Invisible Projected Tags
  • Preprint
  • File available

March 2022

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Liang Han

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Augmented reality (AR) technology has been introduced into the robotics field to narrow the visual gap between indoor and outdoor environments. However, without signals from satellite navigation systems, flight experiments in these indoor AR scenarios need other accurate localization approaches. This work proposes a real-time centimeter-level indoor localization method based on psycho-visually invisible projected tags (IPT), requiring a projector as the sender and quadrotors with high-speed cameras as the receiver. The method includes a modulation process for the sender, as well as demodulation and pose estimation steps for the receiver, where screen-camera communication technology is applied to hide fiducial tags using human vision property. Experiments have demonstrated that IPT can achieve accuracy within ten centimeters and a speed of about ten FPS. Compared with other localization methods for AR robotics platforms, IPT is affordable by using only a projector and high-speed cameras as hardware consumption and convenient by omitting a coordinate alignment step. To the authors' best knowledge, this is the first time screen-camera communication is utilized for AR robot localization.

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