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Advanced Fuzzy Potential Field Method for Mobile Robot Obstacle Avoidance.

Park JW, Kwak HJ, Kang YC, Kim DW - Comput Intell Neurosci (2016)

Bottom Line: An advanced fuzzy potential field method for mobile robot obstacle avoidance is proposed.The potential field method primarily deals with the repulsive forces surrounding obstacles, while fuzzy control logic focuses on fuzzy rules that handle linguistic variables and describe the knowledge of experts.This study also examines the rule-explosion problem of conventional fuzzy logic and assesses the performance of our proposed AFPFM through simulations carried out using a mobile robot.

View Article: PubMed Central - PubMed

Affiliation: Department of Electronic Engineering, Incheon National University, Incheon 402-752, Republic of Korea.

ABSTRACT
An advanced fuzzy potential field method for mobile robot obstacle avoidance is proposed. The potential field method primarily deals with the repulsive forces surrounding obstacles, while fuzzy control logic focuses on fuzzy rules that handle linguistic variables and describe the knowledge of experts. The design of a fuzzy controller--advanced fuzzy potential field method (AFPFM)--that models and enhances the conventional potential field method is proposed and discussed. This study also examines the rule-explosion problem of conventional fuzzy logic and assesses the performance of our proposed AFPFM through simulations carried out using a mobile robot.

No MeSH data available.


Block diagram of the advanced fuzzy controller with distributed structure and additional control inputs.
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fig9: Block diagram of the advanced fuzzy controller with distributed structure and additional control inputs.

Mentions: Based on these control strategies and the design scheme of the distributed fuzzy controller (refer to Figure 7), the structure of the fuzzy controller for the AFPFM can be designed as shown in Figure 9, and the advanced fuzzy rules for the AFPFM are designed as follows:(24) p,q,r,sth  Rule  Rp,q,r,s: IF  dp  is  μdp,q,  ψp  is  μψp,r,  ϕp  is  μϕp,s THEN  yp,q,r,s=fAFPFMp,q,r,sdp,where p = 1,…, n and q, r, s = 1,…, m. Furthermore, the repulsive force > of these advanced fuzzy rules can be written as follows:(25)f~rep=−∑p=1n∑q=1m∑r=1m∑s=1mwp,q,r,syp,q,r,s/∑q=1m∑r=1m∑s=1mwp,q,r,sn,where(26)fAFPFMp,q,r,sdp=k~repp,q,r,s∑i=1nε+didmaxdmaxε+dp1dp−1dmaxsp,wp,q,r,s=μdp,qdp∧μψp,rψp∧μϕp,sϕp.The magnitude of the repulsive forces can be handled by the positive parameter >, and these repulsive forces with various scale factors > can significantly improve the operational performance of the PFM and the FPFM.


Advanced Fuzzy Potential Field Method for Mobile Robot Obstacle Avoidance.

Park JW, Kwak HJ, Kang YC, Kim DW - Comput Intell Neurosci (2016)

Block diagram of the advanced fuzzy controller with distributed structure and additional control inputs.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4829793&req=5

fig9: Block diagram of the advanced fuzzy controller with distributed structure and additional control inputs.
Mentions: Based on these control strategies and the design scheme of the distributed fuzzy controller (refer to Figure 7), the structure of the fuzzy controller for the AFPFM can be designed as shown in Figure 9, and the advanced fuzzy rules for the AFPFM are designed as follows:(24) p,q,r,sth  Rule  Rp,q,r,s: IF  dp  is  μdp,q,  ψp  is  μψp,r,  ϕp  is  μϕp,s THEN  yp,q,r,s=fAFPFMp,q,r,sdp,where p = 1,…, n and q, r, s = 1,…, m. Furthermore, the repulsive force > of these advanced fuzzy rules can be written as follows:(25)f~rep=−∑p=1n∑q=1m∑r=1m∑s=1mwp,q,r,syp,q,r,s/∑q=1m∑r=1m∑s=1mwp,q,r,sn,where(26)fAFPFMp,q,r,sdp=k~repp,q,r,s∑i=1nε+didmaxdmaxε+dp1dp−1dmaxsp,wp,q,r,s=μdp,qdp∧μψp,rψp∧μϕp,sϕp.The magnitude of the repulsive forces can be handled by the positive parameter >, and these repulsive forces with various scale factors > can significantly improve the operational performance of the PFM and the FPFM.

Bottom Line: An advanced fuzzy potential field method for mobile robot obstacle avoidance is proposed.The potential field method primarily deals with the repulsive forces surrounding obstacles, while fuzzy control logic focuses on fuzzy rules that handle linguistic variables and describe the knowledge of experts.This study also examines the rule-explosion problem of conventional fuzzy logic and assesses the performance of our proposed AFPFM through simulations carried out using a mobile robot.

View Article: PubMed Central - PubMed

Affiliation: Department of Electronic Engineering, Incheon National University, Incheon 402-752, Republic of Korea.

ABSTRACT
An advanced fuzzy potential field method for mobile robot obstacle avoidance is proposed. The potential field method primarily deals with the repulsive forces surrounding obstacles, while fuzzy control logic focuses on fuzzy rules that handle linguistic variables and describe the knowledge of experts. The design of a fuzzy controller--advanced fuzzy potential field method (AFPFM)--that models and enhances the conventional potential field method is proposed and discussed. This study also examines the rule-explosion problem of conventional fuzzy logic and assesses the performance of our proposed AFPFM through simulations carried out using a mobile robot.

No MeSH data available.