9 citations · 38 across the 19 of their papers we have counts for
7 papers · 1 filter
Generative Adversarial Network based Heuristics for Sampling-based Path Planning
Tianyi Zhang, Jiankun Wang, Max Q. -H. Meng
Sampling-based path planning is a popular methodology for robot path planning. With a uniform sampling strategy to explore the state space, a feasible path can be found without the…
Efficient Heuristic Generation for Robot Path Planning with Recurrent Generative Model
Zhaoting Li, Jiankun Wang, Max Q. -H. Meng
Robot path planning is difficult to solve due to the contradiction between optimality of results and complexity of algorithms, even in 2D environments. To find an optimal path, the…
Conditional Generative Adversarial Networks for Optimal Path Planning
Nachuan Ma, Jiankun Wang, Max Q. -H. Meng
Path planning plays an important role in autonomous robot systems. Effective understanding of the surrounding environment and efficient generation of optimal collision-free path ar…
Search-Based Online Trajectory Planning for Car-like Robots in Highly Dynamic Environments
Jiahui Lin, Tong Zhou, Delong Zhu +2
This paper presents a search-based partial motion planner to generate dynamically feasible trajectories for car-like robots in highly dynamic environments. The planner searches for…
Online State-Time Trajectory Planning Using Timed-ESDF in Highly Dynamic Environments
Delong Zhu, Tong Zhou, Jiahui Lin +2
Online state-time trajectory planning in highly dynamic environments remains an unsolved problem due to the unpredictable motions of moving obstacles and the curse of dimensionalit…
Pedestrian Motion Tracking by Using Inertial Sensors on the Smartphone
Yingying Wang, Hu Cheng, Max Q. H. Meng
Inertial Measurement Unit (IMU) has long been a dream for stable and reliable motion estimation, especially in indoor environments where GPS strength limits. In this paper, we prop…