Online Trajectory Planning and Control of a MAV Payload System in Dynamic Environments

Online Trajectory Planning and Control of a MAV Payload System in Dynamic Environments: A Non-Linear Model Predictive Control Approach

Potdar, Nikhil (TU Delft Aerospace Engineering)

de Croon, G.C.H.E. (mentor)
Alonso Mora, J. (mentor)
de Visser, C.C. (graduation committee)

Delft University of Technology

Aerospace Engineering | Control & Simulation

2018-03-08

Micro Aerial Vehicles (MAVs) are increasingly being used for aerial transportation in remote and urban spaces where portability can be exploited to reach previously inaccessible and inhospitable spaces. Current approaches to MAV swung payload system path planning have primarily focused on pre-generating (agile) collision-free, or conservative minimal-swing trajectories in static environments. However, these approaches have failed to address the prospect of online re-planning in uncertain and dynamic environments which is a prerequisite for real-world deployability. This article describes a novel Non-Linear Model Predictive Controller (NMPC) for online, agile and closed-loop local trajectory planning and control addressing the limitations mentioned of contemporary approaches. We integrate the controller in a full system framework and demonstrate the algorithm’s effectiveness in simulation and experimental studies. Results show the scalability and adaptability of our method to various dynamic setups with repeatable performance over several complex tasks which include flying through a narrow opening and avoiding moving humans.

Autonomous Vehicles
Micro Aerial Vehicle
Model Predictive Control
Optimal control
Collision Avoidance
Dynamic Environment
MAV

http://resolver.tudelft.nl/uuid:28774acc-89e7-44a8-be43-b06d2db0056c

2019-03-31

Student theses

master thesis

© 2018 Nikhil Potdar