Research progress and prospect of motion planning technology for aerial manipulators

By establishing continuous or transient physical contact with the environment, aerial manipulators have expanded from traditional information acquisition platforms to complex interactive systems with active operation capabilities, evolving from “passive sensing” to “active operation”. They have broad application prospects in complex interaction scenarios of large-scale energy and transportation infrastructure such as bridges, power grids, and oil and gas pipelines. Compared with non-contact flight operations, contact operations involve significant dynamic coupling, contact force constraints, and multi-modal motion switching. The introduced high-dimensional nonlinear constraints limit the feasible solution space of motion planning and restrict the autonomy and stability of the system. To address these challenges, this paper systematically reviews the research progress in the field of motion planning for aerial manipulators. Firstly, starting from the system architecture, this paper analyzes the influences of various flight platform configurations and operation mechanisms on the plannable space and operation capability. Secondly, it summarizes system modeling methods for motion planning, contact dynamics modeling, and various task planning constraints. On this basis, focusing on the planning requirements of contact operation tasks, three mainstream types of motion planning algorithms, namely sampling-based, optimization-based, and learning-based algorithms, are introduced respectively. Their development trends are analyzed, and their applicability and limitations in high-dimensional state search, dynamic constraint handling, and real-time replanning are compared. Finally, the challenges faced by aerial manipulators are summarized and future development trends are prospected.