10 accepted papers
Peripheral nerve injuries represent a significant clinical challenge in reconstructive surgery, traumatology, and neurosurgery, often leading to permanent sensorimotor deficits and diminished life quality. Thus, achieving precise epineurial suturing without nerve fascicle damage and tension remains …
Miniature adhesive patches (MAPs) are widely used in medicine for tissue repair, wound healing, and biosensing applications. Despite considerable advances in medical robotics, the automated in vivo delivery of MAPs remains a formidable challenge due to the intricate nature of biological environments
Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cultural contexts, respect local sensitivities, and support low-resource languages, all while effectively integrating corr…
In drone racing, the time-minimum trajectory is affected by the drone’s capabilities, the layout of the race track, and the configurations of the gates (e.g., their shapes and sizes). However, previous studies neglect the configuration of the gates, simply rendering drone racing a waypoint-passing t…
Motion planning in unknown environments suffers from the limited sensing range of cameras and occlusions. Therefore, perception awareness (PA) should be fully considered to ensure flight safety. Specifically, the unknown part of the planned trajectory should be sensed in advance (visibility constrai
Ensemble sampling serves as a practical approximation to Thompson sampling when maintaining an exact posterior distribution over model parameters is computationally intractable. In this paper, we establish a regret bound that ensures desirable behavior when ensemble sampling is applied to the linear…
Information-directed sampling (IDS) has recently demonstrated its potential as a data-efficient reinforcement learning algorithm. However, it is still unclear what is the right form of information ratio to optimize when contextual information is available. We investigate the IDS design through two c…
We present LINS, a lightweight lidar-inertial state estimator, for real-time ego-motion estimation. The proposed method enables robust and efficient navigation for ground vehicles in challenging environments, such as feature-less scenes, via fusing a 6-axis IMU and a 3D lidar in a tightly-coupled sc…
In this paper, we address the issue of pedestrian tracking in crowd scenarios. People in close social relationships tend to act as a group which is a great challenge to individually discriminate and track pedestrians on a LiDAR system. In this paper, we integrally model groups of people and track th…
The expected improvement (EI) algorithm is a popular strategy for information collection in optimization under uncertainty. The algorithm is widely known to be too greedy, but nevertheless enjoys wide use due to its simplicity and ability to handle uncertainty and noise in a coherent decision theore…