An End-Effector-Oriented Coupled Motion Planning Method for Aerial Manipulators in Constrained Environments

The aerial manipulator, composed of a multirotor and a robotic arm, could provide extra active operation capability and has the potential for applications in both military and civilian fields. Due to the complex working scenarios, planning a safe and reliable motion trajectory for aerial manipulators is of great importance. To achieve target grasping with aerial manipulators in complex environments, a coupled motion planning method for the aerial manipulator is proposed in this article, which conducts the motion planning for the multirotor and the robotic arm simultaneously. Specifically, the aerial manipulator is considered as enclosed by a convex polyhedron other than a big sphere so as to reduce the conservatism of the trajectory. Furthermore, the trajectory of the aerial manipulator could be represented by a set of polynomial functions of the flat outputs, including the position and the yaw angle of the multirotor and the joint angles of the robotic arm. Utilizing polynomial-based trajectory representation for both the multirotor's and the robotic arm's states simplifies the optimization problem and ensures dynamic feasibility. The simulation and experimental results show the effectiveness of the proposed method. Unlike the other works that only consider the position of the end-effector, the proposed method also takes into account the orientation of the end-effector as well, resulting in improved performance in grasping tasks.

Authors

Institutions

Publication Details

Journal
IEEE/ASME Transactions on Mechatronics
Published
2025-03-28
DOI
https://doi.org/10.1109/tmech.2025.3550562
Citations
2
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
2.55

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An End-Effector-Oriented Coupled Motion Planning Method for Aerial Manipulators in Constrained Environments

Yi Chai, Zhichao Yang, Zhaopeng Zhang, Hai Yu et al.
2 citations
IEEE/ASME Transactions on Mechatronics
Robotic Path Planning Algorithms
2.55
article

An End-Effector-Oriented Coupled Motion Planning Method for Aerial Manipulators in Constrained Environments

Yi Chai, Zhichao Yang, Zhaopeng Zhang, Hai Yu, Yongchun Fang, Jianda Han, Xiao Liang
article en
2 citations

Abstract

The aerial manipulator, composed of a multirotor and a robotic arm, could provide extra active operation capability and has the potential for applications in both military and civilian fields. Due to the complex working scenarios, planning a safe and reliable motion trajectory for aerial manipulators is of great importance. To achieve target grasping with aerial manipulators in complex environments, a coupled motion planning method for the aerial manipulator is proposed in this article, which conducts the motion planning for the multirotor and the robotic arm simultaneously. Specifically, the aerial manipulator is considered as enclosed by a convex polyhedron other than a big sphere so as to reduce the conservatism of the trajectory. Furthermore, the trajectory of the aerial manipulator could be represented by a set of polynomial functions of the flat outputs, including the position and the yaw angle of the multirotor and the joint angles of the robotic arm. Utilizing polynomial-based trajectory representation for both the multirotor's and the robotic arm's states simplifies the optimization problem and ensures dynamic feasibility. The simulation and experimental results show the effectiveness of the proposed method. Unlike the other works that only consider the position of the end-effector, the proposed method also takes into account the orientation of the end-effector as well, resulting in improved performance in grasping tasks.

IEEE/ASME Transactions on MechatronicsVol. 30(6)
Nankai University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Tianjin City
Sustainable cities and communities
Openalex Percentile: Top 12%
Robotic Path Planning Algorithms
2.55
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.