KinoJGM: A framework for efficient and accurate quadrotor trajectory generation and tracking in dynamic environments

02/24/2022
by   Yanran Wang, et al.
0

Unmapped areas and aerodynamic disturbances render autonomous navigation with quadrotors extremely challenging. To fly safely and efficiently, trajectory planners and trackers must be able to navigate unknown environments with unpredictable aerodynamic effects in real-time. When encountering aerodynamic effects such as strong winds, most current approaches to quadrotor trajectory planning and tracking will not attempt to deviate from a determined plan, even if it is risky, in the hope that any aerodynamic disturbances can be resisted by a robust controller. This paper presents a novel systematic trajectory planning and tracking framework for autonomous quadrotors. We propose a Kinodynamic Jump Space Search (Kino-JSS) to generate a safe and efficient route in unknown environments with aerodynamic disturbances. A real-time Gaussian Process is employed to model the effects of aerodynamic disturbances, which we then integrate with a Model Predictive Controller to achieve efficient and accurate trajectory optimization and tracking. We demonstrate our system to improve the efficiency of trajectory generation in unknown environments by up to 75% in the cases tested, compared with recent state-of-the-art. We also demonstrate that our system improves the accuracy of tracking in selected environments with unpredictable aerodynamic effects.

READ FULL TEXT

page 1

page 2

page 5

page 6

research
02/14/2021

FaSTrack: a Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking

Real-time, guaranteed safe trajectory planning is vital for navigation i...
research
02/10/2021

Data-Driven MPC for Quadrotors

Aerodynamic forces render accurate high-speed trajectory tracking with q...
research
05/14/2022

Interpretable Stochastic Model Predictive Control using Distributional Reinforced Estimation for Quadrotor Tracking Systems

This paper presents a novel trajectory tracker for autonomous quadrotor ...
research
02/22/2023

Trustworthy Reinforcement Learning for Quadrotor UAV Tracking Control Systems

Simultaneously accurate and reliable tracking control for quadrotors in ...
research
09/16/2023

Trajectory Tracking Control of Skid-Steering Mobile Robots with Slip and Skid Compensation using Sliding-Mode Control and Deep Learning

Slip and skid compensation is crucial for mobile robots' navigation in o...
research
06/20/2019

Autonomous Navigation of MAVs in Unknown Cluttered Environments

This paper presents an autonomous navigation framework for reaching a go...
research
05/12/2023

Double-Iterative Gaussian Process Regression for Modeling Error Compensation in Autonomous Racing

Autonomous racing control is a challenging research problem as vehicles ...

Please sign up or login with your details

Forgot password? Click here to reset