Name
Abstract | ||
|---|---|---|
Trajectory planning in complex environments with different kinds of obstacles, like static obstacles, dynamic obstacles and noncooperative agents, is of great pratical importance for Unmanned Aircraft Vehicle (UAV). Although various algorithms are proposed to solve the obstacle avoidance problem, these methods only consider one or two kinds of obstacles. In this paper, a novel algorithm is proposed to plan a trajectory for UAV in such an environment which simultaneously includes static obstacles, dynamic obstacles and especially noncooperative agents. Besides, we consider different types of approach modes of noncooperative agents and propose corresponding strategies to avoid collisions with them. A set-valued filter-based method is proposed to predict the position of dynamic obstacles and noncooperative agents whose motion model is not available to UAV. Meanwhile, the measurement noise is considered in the set-valued filter to improve the safety of UAV. Some simulations are implemented to verify the effectiveness of the proposed method and they confirm that the proposed method can plan a safe trajectory for UAV in complex environments. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/IECON43393.2020.9255322 | IECON 2020: THE 46TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY |
Keywords | DocType | ISSN |
trajectory planning, collision avoidance, noncooperative agent, set-valued filter | Conference | 1553-572X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hailong Qian | 1 | 0 | 0.34 |
| Weimin Zhong | 2 | 79 | 14.18 |
| Chaoqiang Zhao | 3 | 2 | 1.38 |
| Wenle Zhang | 4 | 0 | 0.34 |
| Yang Tang | 5 | 392 | 21.87 |