8 accepted papers
State-of-the-art (SOTA) video denoising methods employ multi-frame simultaneous denoising mechanisms, resulting in significant delays (e.g., 16 frames), making them impractical for real-time cameras. To overcome this limitation, we propose a multi-fusion gated recurrent Transformer network (GRTN) th…
Robust state estimation is a fundamental research topic in robotics. Existing approaches like robust kernels combined with iteratively re-weighted least squares (IRLS) often require heuristic parameter selection and extensive fine-tuning. In this manuscript, we propose a novel method that optimizes
We present a fast and versatile feature-based LiDAR odometry method using local quadratic surface approximation and point-to-surface alignment. Unlike most feature-based methods, our approach approximates the local geometry of the LiDAR scan as a quadratic surface to mitigate performance degradation
Due to the presence of ambiguities caused by sensor noise and structural similarity, simultaneous localization and mapping (SLAM) observation models are typically multimodal. The multimodal inference process can be directly dealt with by belief propagation (BP) using weighted Gaussian mixture messag…
Applying deep reinforcement learning to physical systems, as opposed to learning in simulation, presents additional challenges in terms of sample efficiency and safety. Collecting large amounts of hardware demonstration data is time-consuming and the exploratory behavior of reinforcement learning al…
Parametric dynamic movement primitives (PDMPs) are powerful motion representation algorithms, which encode multiple demonstrations and generalize them. As an online trajectory from PDMPs emulates the provided demonstrations, managing the safety guarantee of the demonstrations for a given scenario is
This paper describes a vision-based target tracking method for a skid-steer vehicle. With the development of deep reinforcement learning, many researchers have tried to generate an end-to-end policy to control the mobile robot from a raw pixel image data. However, the action in most research only co…
This paper presents a motion planning approach for cooperative transportation using aerial robots. We describe a framework based on Parametric Dynamic Movement Primitives (PDMPs) for coordinating multiple aerial robots and their manipulators quickly in an environment cluttered with obstacles. In ord…