EDBT 2026 Demo / reviewers in the wild / expert
Yi Hsuan Hsiao
dblp:233/0316 · also Yi-Hsuan Hsiao
· DBLP profile ↗
4ranked-venue papers
2as first author
3since 2021 · last 2023
0000-0002-1593-7969ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 4 · 2 first-author · 3 since 2021Systems, architecture and hardware · 4 · 2 first-author · 3 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Heading Control of a Long-Endurance Insect-Scale Aerial Robot Powered by Soft Artificial MusclesabstractAerial insects demonstrate fast and precise heading control when they perform body saccades and rapid escape maneuvers. While insect-scale micro-aerial-vehicles (IMAVs) have demonstrated early results on heading control, their flight endurance and heading angle tracking accuracy remain far inferior to that of natural fliers. In this work, we present a long endurance sub-gram aerial robot that can demonstrate effective heading control during hovering flight. Through using a tilted wing stroke-plane design, our robot demonstrates a 10-second flight where it tracks a desired yaw trajectory with maximum and root-mean-square (RMS) error of$\boldsymbol{14.2^{\circ}}$and$\boldsymbol{5.8}^{\mathrm{o}}$. The new robot design requires 7% higher lift forces for enabling heading angle control, which creates higher stress on wing hinges and adversely influences robot endurance. To address this challenge, we developed novel 3-layered wing hinges that exhibit 1.82 times improvement of lifetime. With the new wing hinges, our robot demonstrates a 40-second hovering flight - the longest among existing sub-gram IMAVs. These results represent substantial improvement of flight capabilities in soft-actuated IMAVs, showing the potential of operating these insect-like fliers in cluttered natural environments. Yi Hsuan Hsiao, Suhan Kim, Zhijian Ren, Yufeng Chen 0003 |
ICRA | 1 |
| 2023 | A lightweight high-voltage boost circuit for soft-actuated micro-aerial-robotsabstractFlight is an energetically expensive task. While aerial insects can effortlessly fly through natural environments, achieving power autonomous flights in insect-scale robots remains a major challenge. In prior works, we developed soft-actuated insect-scale aerial robots that demonstrated unique capabilities such as in-flight collision recovery and somersaults. However, the soft dielectric elastomer actuators (DEAs) have low efficiency (600 V). These properties represent formidable obstacles for soft aerial robots to achieve power autonomous flights. In this work, we developed a 127 mg boost circuit that can convert a 7.7 V DC input into a 600 V and 400 Hz output for driving a 120 mg DEA. It has an equivalent capacitance and resistance of 20 nF and 5$\mathbf{k}\Omega$, respectively. The DEA is assembled into a 158 mg aerial robot, which can demonstrate liftoff while carrying the boost circuit as a payload. Although the robot remains tethered to an off-board power supply, this result represents a first step towards achieving power autonomy in soft aerial robots. Zhijian Ren, Suhan Kim, Yi Hsuan Hsiao, Jeffrey Lang, Yufeng Chen 0003 |
ICRA | 4 |
| 2023 | Robust, High-Rate Trajectory Tracking on Insect-Scale Soft-Actuated Aerial Robots with Deep-Learned Tube MPCabstractAccurate and agile trajectory tracking in sub-gram Micro Aerial Vehicles (MAVs) is challenging, as the small scale of the robot induces large model uncertainties, demanding robust feedback controllers, while the fast dynamics and computational constraints prevent the deployment of computationally expensive strategies. In this work, we present an approach for agile and computationally efficient trajectory tracking on the MIT SoftFly [1], a sub-gram MAV (0.7 grams). Our strategy employs a cascaded control scheme, where an adaptive attitude controller is combined with a neural network (NN) policy trained to imitate a trajectory tracking robust tube model predictive controller (RTMPC). The NN policy is obtained using our recent work [2], which enables the policy to preserve the robustness of RTMPC, but at a fraction of its computational cost. We experimentally evaluate our approach, achieving position Root Mean Square Errors (RMSEs) lower than 1.8 cm even in the more challenging maneuvers, obtaining a 60% reduction in maximum position error compared to [3], and demonstrating robustness to large external disturbances. Andrea Tagliabue, Yi Hsuan Hsiao, Urban Fasel, J. Nathan Kutz, Steven L. Brunton, Yufeng Chen 0003, Jonathan P. How |
ICRA | 2 |
| 2018 | Ceiling Effects for Surface Locomotion of Small RotorcraftabstractMotivated by the potential of bimodal aerial and surface locomotion as an energy saving strategy for small flying robots, we investigate the effects of a flat overhang surface in the vicinity of a spinning propeller. We employ the classical momentum theory and the blade element method to describe the “ceiling effects” in regards to the generated thrust, power, and rotational speed of the propeller in terms of a normalized distance between the ceiling and the propeller. Validating experiments were performed on a benchtop setup, and the results are in agreement with the proposed models. The presence of a ceiling was found to reduce the power consumption by more than a factor of three for the same thrust force. Overall, our findings show promise, paving the way for the use of perching maneuvers by small rotorcraft to extend their missions. Yi Hsuan Hsiao, Pakpong Chirarattananon |
IROS | 1 |