6 accepted papers
While hyperspectral images (HSI) benefit from numerous spectral channels that provide rich information for classification, the increased dimensionality and sensor variability make them more sensitive to distributional discrepancies across domains, which in turn can affect classification performance.
Global trajectory planning is crucial for long-range formation navigation tasks of multi-robot systems in efficiency improvement and energy saving, whose main challenges are the joint space constraints of the whole team and the long-range deployment. To overcome the above difficulties, we reformulat
This letter introduces an innovative vehicle motion planning method that leverages the integration of rule-based insights to significantly improve closed-loop performance within a learning-based framework. We first employ rule-based methods to heuristically search and generate a diverse set of traje
Goal-reaching in unknown environments is one of the essential tasks in robot applications. Large-scale perception and long-horizon decision-making are the keys to solving this task as the operation scope expands or complexity rises. Existing navigation methods may suffer from degraded performance in
Image-goal navigation in unknown environments with sensor error is of considerable difficulty for autonomous robots. In this paper, we propose a drift-resisting topo-metric graph to map the environment and localize the robot using only relative poses. The error-sharing mechanism under this represent…
Grasp detection based on deep learning has been a research hot spot in recent years. The performance of grasping detection models relies on high-quality, large-scale grasp datasets. Taking comprehensive consideration of quality, extendability, and annotation cost, metric-based simulation methodolog…