Near Time-Optimal Trajectory Generation for Multirotors using Numerical Optimization and Safe Corridors

Trajectory generation is a fundamental problem for every type of robot. In most applications, the robots should reach their goals in the minimum time possible. Time-optimal trajectory generation allows us to solve this problem. The generation of such trajectories for multirotors has gained traction...

Full description

Saved in:
Bibliographic Details
Published inJournal of intelligent & robotic systems Vol. 105; no. 1; p. 20
Main Authors Toumieh, Charbel, Lambert, Alain
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.05.2022
Springer Nature B.V
Subjects
Acceleration
Aerodynamic drag
Algorithms
Artificial Intelligence
Control
Electrical Engineering
Engineering
Evacuations & rescues
Gravity
Mechanical Engineering
Mechatronics
Nonlinearity
Optimization
Polynomials
Racing
Robotics
Robots
Search and rescue missions
Short Paper
Topical collection on Unmanned Systems
Trajectory optimization
Transportation corridors
Motion planning
Modelling
Online AccessGet full text
ISSN0921-0296
1573-0409
DOI10.1007/s10846-022-01625-0

Cover

More Information
Summary:Trajectory generation is a fundamental problem for every type of robot. In most applications, the robots should reach their goals in the minimum time possible. Time-optimal trajectory generation allows us to solve this problem. The generation of such trajectories for multirotors has gained traction with new applications in transport, delivery and search and rescue missions, as well as other applications in sports and entertainment such as drone racing. The current state-of-the-art is heavily based on polynomial methods and most methods choose a conservative approach when limiting the velocity or acceleration as a way to account for nonlinearities and guarantee feasibility, which limits time optimality and trajectory speed. We overcome this limitation by proposing a new formulation for multirotors trajectory generation that takes into account nonlinearities such as gravity and aerodynamic drag, It allows us to provide more time-optimal solutions then the state-of-the-art. We present an algorithm that uses our new formulation for near time-optimal trajectory generation for multirotors subject to obstacles/path constraints. We validate our approach using a state of the art simulator and compare it with other time-optimal trajectory generation methods.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0921-0296
1573-0409
DOI:10.1007/s10846-022-01625-0