4 accepted papers
Autonomous navigation social robots need to track pedestrian movements in real-time with high precision to optimize path planning and avoid collisions. However, the main challenge of pedestrian tracking lies in the significant variations in human posture, which differ from rigid-body structures like
High-fidelity reconstruction is crucial for dense SLAM. Recent popular methods utilize 3D Gaussian splatting (3D GS) techniques for RGB, depth, and semantic reconstruction of scenes. However, these methods ignore issues of detail and consistency in different parts of the scene. To address this, we p
In the context of indoor crowd navigation for mobile robots, the generation of spatial-temporally complete trajectories gives the robot a wider range of options, thereby improving the robustness and safety of navigation. Focused on this topic, this letter presents an incremental optimization framewo
In human-aware navigation, the robot tacitly games with humans, balancing safety and efficiency according to human intentions. Poor balance or bad intent recognition causes the robot to stop conservatively or advance rashly, resulting in a deadlock or even a collision respectively. To address the is…