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U Kei Cheang

Publications and source records attributed to U Kei Cheang.

4 recordsLinked to original sources

PerchRL: Vision-Based Agile Perching on Inclined Platforms under Rapid and Irregular Motion

Autonomous vision-based perching of quadrotors on moving inclined platforms is critical for air-ground collaboration but remains challenging due to the limited field of view (FOV). In this paper, we propose PerchRL, a reinforcement learning (RL) framework for vision-based agile perching on inclined platforms under rapid and irregular motion. Specifically, we employ a two-stage learning strategy consisting of state-based pre-training followed by vision-based fine-tuning. To improve generalization across diverse platform motions, we employ randomized platform trajectories to prevent overfitting and temporal augmentation methods to capture latent motion patterns from historical observations. During vision-based fine-tuning, a hybrid learning framework consisting of visibility-aware state augmentation and active perception rewards is presented to improve robustness under intermittent visual loss. Extensive simulation and real-world experiments demonstrate the feasibility, stability, and real-time performance of PerchRL, while successful deployment across distinct quadrotor platforms further validates its adaptability. The source code will be released to benefit the community.

cs.RO

A transformable slender microrobot inspired by nematode parasites for interventional endovascular surgery

Cardiovascular diseases account for around 17.9 million deaths per year globally, the treatment of which is challenging considering the confined space and complex topology of the vascular network and high risks during operations. Robots, although promising, still face the dilemma of possessing versatility or maneuverability after decades of development. Inspired by nematodes, the parasites living, feeding, and moving in the human body's vascular system, this work develops a transformable slender magnetic microrobot. Based on the experiments and analyses, we optimize the fabrication and geometry of the robot and finally create a slender prototype with an aspect ratio larger than 100 (smaller than 200 microns in diameter and longer than 20 mm in length), which possesses uniformly distributed magnetic beads on the body of an ultrathin polymer string and a big bead on the head. This prototype shows great flexibility (largest curvature 0.904 mm-1) and locomotion capability (the maximum speed: 125 mm/s). Moreover, the nematode-inspired robot can pass through sharp turns with a radius of 0.84 mm and holes distributed in three-dimensional (3D) space. We also display the potential application in interventional surgery of the microrobot by navigating it through a narrow blood vessel mold to wrap and transport a drug (95 times heavier than the robot) by deforming the robot's slender body and releasing the drug to the aim position finally. Moreover, the robot also demonstrates the possible applications in embolization by transforming and winding itself into an aneurysms phantom and exhibits its outstanding injectability by being successfully withdrawn and injected through a medical needle (diameter: 1.2 mm) of a syringe.

cs.RO

Injection and Imaging of Achiral Microswimmers in Zebrafish

Achieving stable in vivo locomotion is essential for using magnetically actuated microswimmers for biomedical applications; however, while existing microswimmers have excellent motion control in vitro, their motion is greatly hindered inside living organisms. Moreover, previous work had only visually demonstrated in vivo motion through gradient pulling or rolling, but not swimming. This study investigated the injection and imaging of the achiral planar microswimmers (APMs) inside a live zebrafish embryo. The APMs can be actuated under a rotating magnetic field to generate a forward thrust at low Reynolds number environment. Combined with a safe injection technique and clear in vivo imaging at high resolution, it would be possible to control the swimming motion of APMs inside the zebrafish embryo. This work shows the safe injection and the clear imaging of an APM in a transparent zebrafish model, demonstrating the possibility for follow-up in-depth studies of the swimming motion of microswimmers in vivo.

physics.bio-ph

Biosensing-by-learning Direct Targeting Strategy for Enhanced Tumor Sensitization

Objective:We propose a novel iterative-optimizationinspired direct targeting strategy (DTS) for smart nanosystems, which harness swarms of externally manipulable nanoswimmers assembled by magnetic nanoparticles (MNPs) for knowledgeaided tumor sensitization and targeting. We aim to demonstrate through computational experiments that the proposed DTS can significantly enhance the accumulation of MNPs in the tumor site, which serve as a contrast agent in various medical imaging modalities, by using the shortest possible physiological routes and with minimal systemic exposure. Methods: The epicenter of a tumor corresponds to the global maximum of an externally measurable objective function associated with an in vivo tumor-triggered biophysical gradient; the domain of the objective function is the tissue region at a high risk of malignancy; swarms of externally controllable magnetic nanoswimmers for tumor sensitization are modeled as the guess inputs. The objective function may be resulted from a passive phenomenon such as reduced blood flow or increased kurtosis of microvasculature due to tumor angiogenesis; otherwise, the objective function may involve an active phenomenon such as the fibrin formed during the coagulation cascade activated by tumortargeted "activator" nanoparticles. Subsequently, the DTS can be interpreted from the iterative optimization perspective: guess inputs (i.e., swarms of nanoswimmers) are continuously updated according to the gradient of the objective function in order to find the optimum (i.e., tumor) by moving through the domain (i.e., tissue under screening). Along this line of thought, we propose the computational model based on the gradient descent (GD) iterative method to describe the GD-inspired DTS, which takes into account the realistic in vivo propagation scenario of nanoswimmers.

physics.med-ph