Language measure-theoretic path planning in the presence of dynamic obstacles

Siddharth Sonti, Nurali Virani, Devesh K. Jha, Kushal Mukherjee, Asok Ray

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The paper presents an algorithm to solve goal-directed path planning problems in dynamic and uncertain environments. A grid-based path planning algorithm, called ν*, was formulated in the framework of probabilistic finite state automata (PFSA) from a control-theoretic perspective. The work reported in this paper extends the formulation of path planning in environments with static obstacles to include the presence of dynamic obstacles with stochastic motion models. The framework to solve this problem involves an initial plan that is based on the time-averaged likelihood of dynamic obstacles being present at a particular location. This information is inferred from the stochastic model. Additionally, there is a path re-planning component, based on the current measurements. Results of numerical simulation are presented to demonstrate the efficacy of the proposed concept.

Original languageEnglish (US)
Title of host publication2013 American Control Conference, ACC 2013
Pages5110-5115
Number of pages6
StatePublished - Sep 11 2013
Event2013 1st American Control Conference, ACC 2013 - Washington, DC, United States
Duration: Jun 17 2013Jun 19 2013

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2013 1st American Control Conference, ACC 2013
CountryUnited States
CityWashington, DC
Period6/17/136/19/13

Fingerprint

Motion planning
Finite automata
Electric current measurement
Stochastic models
Planning
Computer simulation

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Sonti, S., Virani, N., Jha, D. K., Mukherjee, K., & Ray, A. (2013). Language measure-theoretic path planning in the presence of dynamic obstacles. In 2013 American Control Conference, ACC 2013 (pp. 5110-5115). [6580632] (Proceedings of the American Control Conference).
Sonti, Siddharth ; Virani, Nurali ; Jha, Devesh K. ; Mukherjee, Kushal ; Ray, Asok. / Language measure-theoretic path planning in the presence of dynamic obstacles. 2013 American Control Conference, ACC 2013. 2013. pp. 5110-5115 (Proceedings of the American Control Conference).
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Sonti, S, Virani, N, Jha, DK, Mukherjee, K & Ray, A 2013, Language measure-theoretic path planning in the presence of dynamic obstacles. in 2013 American Control Conference, ACC 2013., 6580632, Proceedings of the American Control Conference, pp. 5110-5115, 2013 1st American Control Conference, ACC 2013, Washington, DC, United States, 6/17/13.

Language measure-theoretic path planning in the presence of dynamic obstacles. / Sonti, Siddharth; Virani, Nurali; Jha, Devesh K.; Mukherjee, Kushal; Ray, Asok.

2013 American Control Conference, ACC 2013. 2013. p. 5110-5115 6580632 (Proceedings of the American Control Conference).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - The paper presents an algorithm to solve goal-directed path planning problems in dynamic and uncertain environments. A grid-based path planning algorithm, called ν*, was formulated in the framework of probabilistic finite state automata (PFSA) from a control-theoretic perspective. The work reported in this paper extends the formulation of path planning in environments with static obstacles to include the presence of dynamic obstacles with stochastic motion models. The framework to solve this problem involves an initial plan that is based on the time-averaged likelihood of dynamic obstacles being present at a particular location. This information is inferred from the stochastic model. Additionally, there is a path re-planning component, based on the current measurements. Results of numerical simulation are presented to demonstrate the efficacy of the proposed concept.

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Sonti S, Virani N, Jha DK, Mukherjee K, Ray A. Language measure-theoretic path planning in the presence of dynamic obstacles. In 2013 American Control Conference, ACC 2013. 2013. p. 5110-5115. 6580632. (Proceedings of the American Control Conference).