4 accepted papers
Keyframe insertion is critical for the performance and robustness of SLAM systems. However, traditional heuristic-based methods often lead to suboptimal keyframe selection, compromising the accuracy of localization and mapping. To address this, we propose KINND, a lightweight neural network-based fr
Garment manipulation is a significant challenge for robots due to the complex dynamics and potential self-occlusion of garments. Most existing methods of efficient garment unfolding overlook the crucial role of standardization of flattened garments, which could significantly simplify downstream task…
Multi-robot cooperative tracking, as a vital sub-field of multi-robot collaboration, exhibits significant potential in areas such as military reconnaissance and emergency rescue. Conventional dynamic object tracking methods often face issues of incomplete target detection and even loss in complex sc
With the advent of solid-state LiDAR, a series of related studies have boosted the development of Simultaneous Localization and Mapping (SLAM). However, existing methods cannot work well in indoor environments. In the letter, the reflectivity measurement of the solid-state LiDAR is exploited to impr