Incremental Sampling-Based Algorithm for Minimum-Violation Motion Planning

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F13%3A00081960" target="_blank" >RIV/00216224:14330/13:00081960 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/CDC.2013.6760374" target="_blank" >http://dx.doi.org/10.1109/CDC.2013.6760374</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CDC.2013.6760374" target="_blank" >10.1109/CDC.2013.6760374</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Incremental Sampling-Based Algorithm for Minimum-Violation Motion Planning

Popis výsledku v původním jazyce

This paper studies the problem of control strategy synthesis for dynamical systems with differential constraints to fulfill a given reachability goal specification while satisfying a set of safety rules. Particular attention is devoted to goals that become feasible only if a subset of the safety rules are violated. The proposed algorithm computes a control law, that minimizes the level of unsafety while the desired goal is guaranteed to be reached. This problem is motivated by an autonomous car navigating an urban environment while following rules of the road such as "always travel in right lane" and "do not change lanes frequently". Ideas behind sampling based motion-planning algorithms, such as Probabilistic Road Maps (PRMs) and Rapidly-exploring Random Trees (RRTs), are employed to incrementally construct a finite concretization of the dynamics as a durational Kripke structure.

Název v anglickém jazyce

Incremental Sampling-Based Algorithm for Minimum-Violation Motion Planning

Popis výsledku anglicky

This paper studies the problem of control strategy synthesis for dynamical systems with differential constraints to fulfill a given reachability goal specification while satisfying a set of safety rules. Particular attention is devoted to goals that become feasible only if a subset of the safety rules are violated. The proposed algorithm computes a control law, that minimizes the level of unsafety while the desired goal is guaranteed to be reached. This problem is motivated by an autonomous car navigating an urban environment while following rules of the road such as "always travel in right lane" and "do not change lanes frequently". Ideas behind sampling based motion-planning algorithms, such as Probabilistic Road Maps (PRMs) and Rapidly-exploring Random Trees (RRTs), are employed to incrementally construct a finite concretization of the dynamics as a durational Kripke structure.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

<a href="/cs/project/LH11065" target="_blank" >LH11065: Řízení a ověřování vlastností komplexních hybridních systémů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the IEEE 52nd Annual Conference on Decision and Control (CDC), 2013

ISBN

9781467357173

ISSN

0191-2216

e-ISSN

—

Počet stran výsledku

8

Strana od-do

3217-3224

Název nakladatele

IEEE

Místo vydání

Florence, Italy

Místo konání akce

Florence, Italy

Datum konání akce

1. 1. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000352223503105