Motion Planning for Multirotor Aerial Vehicles in Plan-based Control Paradigm: a Review

TL;DR

This review paper analyzes various motion planning techniques for multirotor aerial vehicles, focusing on real-time trajectory generation, comparing local and global methods based on key performance metrics.

Contribution

It provides a comprehensive overview of trajectory planning methods, breaking down the problem into subproblems and summarizing key results from 2010 to 2022.

Findings

Trajectory planning problem is segmented into subproblems.

Identified methods address each subproblem effectively.

Summarized timeline of prominent results from 2010-2022.

Abstract

In general, optimal motion planning can be performed both locally and globally. In such a planning, the choice in favour of either local or global planning technique mainly depends on whether the environmental conditions are dynamic or static. Hence, the most adequate choice is to use local planning or local planning alongside global planning. When designing optimal motion planning both local and global, the key metrics to bear in mind are execution time, asymptotic optimality, and quick reaction to dynamic obstacles. Such planning approaches can address the aforesaid target metrics more efficiently compared to other approaches such as path planning followed by smoothing. Thus, the foremost objective of this study is to analyse related literature in order to understand how the motion planning, especially trajectory planning, problem is formulated, when being applied for generating optimal trajectories in real-time for Multirotor Aerial Vehicles (MAVs), impacts the listed metrics. As a result of the research, the trajectory planning problem was broken down into a set of subproblems, and the lists of methods for addressing each of the problems were identified and described in detail. Subsequently, the most prominent results from 2010 to 2022 were summarized and presented in the form of a timeline.