Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments

Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments
Author :
Publisher : Linköping University Electronic Press
Total Pages : 85
Release :
ISBN-10 : 9789179296773
ISBN-13 : 9179296777
Rating : 4/5 (777 Downloads)

Book Synopsis Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments by : Kristoffer Bergman

Download or read book Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments written by Kristoffer Bergman and published by Linköping University Electronic Press. This book was released on 2021-03-16 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the last decades, motion planning for autonomous systems has become an important area of research. The high interest is not the least due to the development of systems such as self-driving cars, unmanned aerial vehicles and robotic manipulators. The objective in optimal motion planning problems is to find feasible motion plans that also optimize a performance measure. From a control perspective, the problem is an instance of an optimal control problem. This thesis addresses optimal motion planning problems for complex dynamical systems that operate in unstructured environments, where no prior reference such as road-lane information is available. Some example scenarios are autonomous docking of vessels in harbors and autonomous parking of self-driving tractor-trailer vehicles at loading sites. The focus is to develop optimal motion planning algorithms that can reliably be applied to these types of problems. This is achieved by combining recent ideas from automatic control, numerical optimization and robotics. The first contribution is a systematic approach for computing local solutions to motion planning problems in challenging unstructured environments. The solutions are computed by combining homotopy methods and direct optimal control techniques. The general principle is to define a homotopy that transforms, or preferably relaxes, the original problem to an easily solved problem. The approach is demonstrated in motion planning problems in 2D and 3D environments, where the presented method outperforms a state-of-the-art asymptotically optimal motion planner based on random sampling. The second contribution is an optimization-based framework for automatic generation of motion primitives for lattice-based motion planners. Given a family of systems, the user only needs to specify which principle types of motions that are relevant for the considered system family. Based on the selected principle motions and a selected system instance, the framework computes a library of motion primitives by simultaneously optimizing the motions and the terminal states. The final contribution of this thesis is a motion planning framework that combines the strengths of sampling-based planners with direct optimal control in a novel way. The sampling-based planner is applied to the problem in a first step using a discretized search space, where the system dynamics and objective function are chosen to coincide with those used in a second step based on optimal control. This combination ensures that the sampling-based motion planner provides a feasible motion plan which is highly suitable as warm-start to the optimal control step. Furthermore, the second step is modified such that it also can be applied in a receding-horizon fashion, where the proposed combination of methods is used to provide theoretical guarantees in terms of recursive feasibility, worst-case objective function value and convergence to the terminal state. The proposed motion planning framework is successfully applied to several problems in challenging unstructured environments for tractor-trailer vehicles. The framework is also applied and tailored for maritime navigation for vessels in archipelagos and harbors, where it is able to compute energy-efficient trajectories which complies with the international regulations for preventing collisions at sea.


Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments Related Books

Exploiting Direct Optimal Control for Motion Planning in Unstructured Environments
Language: en
Pages: 85
Authors: Kristoffer Bergman
Categories:
Type: BOOK - Published: 2021-03-16 - Publisher: Linköping University Electronic Press

GET EBOOK

During the last decades, motion planning for autonomous systems has become an important area of research. The high interest is not the least due to the developm
Sensor Management for Target Tracking Applications
Language: en
Pages: 85
Authors: Per Boström-Rost
Categories:
Type: BOOK - Published: 2021-04-12 - Publisher: Linköping University Electronic Press

GET EBOOK

Many practical applications, such as search and rescue operations and environmental monitoring, involve the use of mobile sensor platforms. The workload of the
Motion Planning in Dynamic Environments
Language: en
Pages: 190
Authors: Kikuo Fujimura
Categories: Computers
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

GET EBOOK

Computer Science Workbench is a monograph series which will provide you with an in-depth working knowledge of current developments in computer technology. Every
On motion planning and control for truck and trailer systems
Language: en
Pages: 98
Authors: Oskar Ljungqvist
Categories:
Type: BOOK - Published: 2019-01-22 - Publisher: Linköping University Electronic Press

GET EBOOK

During the last decades, improved sensor and hardware technologies as well as new methods and algorithms have made self-driving vehicles a realistic possibility
Principles of Robot Motion
Language: en
Pages: 642
Authors: Howie Choset
Categories: Technology & Engineering
Type: BOOK - Published: 2005-05-20 - Publisher: MIT Press

GET EBOOK

A text that makes the mathematical underpinnings of robot motion accessible and relates low-level details of implementation to high-level algorithmic concepts.