3 accepted papers
LiDAR odometry is a pivotal technology in the fields of autonomous driving and autonomous mobile robotics. However, most of the current works focus on nonlinear optimization methods, and still existing many challenges in using the traditional Iterative Extended Kalman Filter (IEKF) framework to tack…
The sim-to-real gap poses a significant challenge in RL-based multi-agent exploration due to scene quantization and action discretization. Existing platforms suffer from the inefficiency in sampling and the lack of diversity in Multi-Agent Reinforcement Learning (MARL) algorithms across different sc…
The selection of step sizes in the progressive Gaussian approximate filter (PGAF) is important, and it is difficult to select optimal values in practical applications. Furthermore, in the PGAF, significant integral approximation errors are generated by the repeated approximate calculations of the Ga…