5 accepted papers
As the potential of multi-robot systems continues to be explored and validated across various real-world applications, such as package delivery, search and rescue, and autonomous exploration, the need to improve the efficiency and quality of task and path planning has become increasingly urgent, par
Autonomous exploration is a critical foundation for unmanned aerial vehicle (UAV) applications such as search and rescue. However, existing methods typically focus only on known spaces or frontiers without considering unknown regions or providing further guidance for the global path, which results i
This work focuses on multi-floor indoor exploration, which remains an open area of research. Compared to traditional methods, recent learning-based explorers have demonstrated significant potential due to their robust environmental learning and modeling capabilities, but most are restricted to 2D en
Multi-agent path finding (MAPF) in dynamic and complex environments is a highly challenging task. Recent research has focused on the scalability of agent numbers or the complexity of the environment. Usually, they disregard the agents' physical constraints or use a differential-driven model. However
Siamese network has been a de facto benchmark framework for 3D LiDAR object tracking with a shared-parametric encoder extracting features from template and search region, respectively. This paradigm relies heavily on an additional matching network to model the cross-correlation/similarity of the tem…