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Journal ArticleDOI

Maneuver-based motion planning for nonlinear systems with symmetries

TLDR
An approach for the efficient solution of motion-planning problems for time-invariant dynamical control systems with symmetries, such as mobile robots and autonomous vehicles, under a variety of differential and algebraic constraints on the state and on the control input.
Abstract
In this paper, we introduce an approach for the efficient solution of motion-planning problems for time-invariant dynamical control systems with symmetries, such as mobile robots and autonomous vehicles, under a variety of differential and algebraic constraints on the state and on the control inputs. Motion plans are described as the concatenation of a number of well-defined motion primitives, selected from a finite library. Rules for the concatenation of primitives are given in the form of a regular language, defined through a finite-state machine called a Maneuver Automaton. We analyze the reachability properties of the language, and present algorithms for the solution of a class of motion-planning problems. In particular, it is shown that the solution of steering problems for nonlinear dynamical systems with symmetries and invariant constraints can be reduced to the solution of a sequence of kinematic inversion problems. A detailed example of the application of the proposed approach to motion planning for a small aerobatic helicopter is presented.

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Citations
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MonographDOI

Planning Algorithms: Introductory Material

TL;DR: This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms, into planning under differential constraints that arise when automating the motions of virtually any mechanical system.
Journal ArticleDOI

Temporal-Logic-Based Reactive Mission and Motion Planning

TL;DR: A framework to automatically generate a hybrid controller that guarantees that the robot can achieve its task when a robot model, a class of admissible environments, and a high-level task or behavior for the robot are provided.
Journal ArticleDOI

Motion planning with sequential convex optimization and convex collision checking

TL;DR: A sequential convex optimization procedure, which penalizes collisions with a hinge loss and increases the penalty coefficients in an outer loop as necessary, and an efficient formulation of the no-collisions constraint that directly considers continuous-time safety are presented.
Journal ArticleDOI

Autonomous Helicopter Aerobatics through Apprenticeship Learning

TL;DR: These apprenticeship learning algorithms have enabled us to significantly extend the state of the art in autonomous helicopter aerobatics, including the first autonomous execution of a wide range of maneuvers, including in-place flips, in- place rolls, loops and hurricanes.
Journal ArticleDOI

Sampling-Based Robot Motion Planning: A Review

TL;DR: The state of the art in motion planning is surveyed and selected planners that tackle current issues in robotics are addressed, for instance, real-life kinodynamic planning, optimal planning, replanning in dynamic environments, and planning under uncertainty are discussed.
References
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Book

A Mathematical Introduction to Robotic Manipulation

TL;DR: In this paper, the authors present a detailed overview of the history of multifingered hands and dextrous manipulation, and present a mathematical model for steerable and non-driveable hands.
Book

Applied optimal control

Book

Nonlinear Systems: Analysis, Stability, and Control

TL;DR: In this article, the authors compare Linear vs. Nonlinear Control of Differential Geometry with Linearization by State Feedback (LSF) by using Linearization and Geometric Non-linear Control (GNC).
Journal ArticleDOI

Stabilization of linear systems with limited information

TL;DR: By relaxing the definition of quadratic stability, it is shown how to construct logarithmic quantizers with only finite number of quantization levels and still achieve practical stability of the closed-loop system.
Journal ArticleDOI

Quantized feedback stabilization of linear systems

TL;DR: A new control design methodology is proposed, which relies on the possibility of changing the sensitivity of the quantizer while the system evolves, which yields global asymptotic stability.