Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots

The path planning and obstacles avoidance in dynamic environments are vitally important problems for auto-navigation of mobile robots. Generally, the dynamic windows approach is one of the commonly used algorithms to solve the above-mentioned problems. Nevertheless, the robustness of dynamic windows...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Yao, Ming [verfasserIn] Deng, Haigang [verfasserIn] Feng, Xianying [verfasserIn] Li, Peigang [verfasserIn] Li, Yanfei [verfasserIn] Liu, Haiyang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	Mobile robot Path planning Dynamic obstacle avoidance Fuzzy logic control method Optimal energy consumption Dynamic window approach

Übergeordnetes Werk:	Enthalten in: Computers & industrial engineering - Amsterdam [u.a.] : Elsevier Science, 1976, 187
Übergeordnetes Werk:	volume:187

DOI / URN:	10.1016/j.cie.2023.109767

Katalog-ID:	ELV066415950

Internformat


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520			\|a The path planning and obstacles avoidance in dynamic environments are vitally important problems for auto-navigation of mobile robots. Generally, the dynamic windows approach is one of the commonly used algorithms to solve the above-mentioned problems. Nevertheless, the robustness of dynamic windows approach is poor, while the generated paths are not smooth. Thus, this paper proposed a fuzzy logic improved dynamic windows approach. Firstly, the energy consumption model of the drive motor is established and used to extend the evaluation function of the dynamic windows approach, which helps to improve the smoothness of generated paths. Secondly, three fuzzy logic controllers are designed based on the directional rules, safety rules and fusion rules respectively to output weight parameters real-time, which improves the robustness. In static and dynamic simulations, maps with sizes of 20 × 20 and 30 × 30 are designed respectively to compare the paths generated by the algorithm proposed in this study with the dynamic windows approach that selects different weight parameters. The results show that although the average calculation time of fuzzy logic improved dynamic windows approach is slightly longer, the robustness is better, the generated path is shorter, and the energy consumption of the drive motors is lower. The LEO ROS mobile robot is selected for the experiments, the results also show that compared with the dynamic windows approach and the time elastic band, the algorithm proposed in this study has better performance in terms of length and smoothness of paths and robustness.
650		4	\|a Mobile robot
650		4	\|a Path planning
650		4	\|a Dynamic obstacle avoidance
650		4	\|a Fuzzy logic control method
650		4	\|a Optimal energy consumption
650		4	\|a Dynamic window approach
700	1		\|a Deng, Haigang \|e verfasserin \|4 aut
700	1		\|a Feng, Xianying \|e verfasserin \|4 aut
700	1		\|a Li, Peigang \|e verfasserin \|4 aut
700	1		\|a Li, Yanfei \|e verfasserin \|4 aut
700	1		\|a Liu, Haiyang \|e verfasserin \|4 aut
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Indexfelder

author_variant	m y my h d hd x f xf p l pl y l yl h l hl
matchkey_str	article:03608352:2023----::mrvdyaiwnosprahaeoeegcnupinaaeetnfzyoicnrlo
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publishDate	2023
allfields	10.1016/j.cie.2023.109767 doi (DE-627)ELV066415950 (ELSEVIER)S0360-8352(23)00791-X DE-627 ger DE-627 rda eng 004 VZ 85.35 bkl 54.80 bkl Yao, Ming verfasserin aut Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The path planning and obstacles avoidance in dynamic environments are vitally important problems for auto-navigation of mobile robots. Generally, the dynamic windows approach is one of the commonly used algorithms to solve the above-mentioned problems. Nevertheless, the robustness of dynamic windows approach is poor, while the generated paths are not smooth. Thus, this paper proposed a fuzzy logic improved dynamic windows approach. Firstly, the energy consumption model of the drive motor is established and used to extend the evaluation function of the dynamic windows approach, which helps to improve the smoothness of generated paths. Secondly, three fuzzy logic controllers are designed based on the directional rules, safety rules and fusion rules respectively to output weight parameters real-time, which improves the robustness. In static and dynamic simulations, maps with sizes of 20 × 20 and 30 × 30 are designed respectively to compare the paths generated by the algorithm proposed in this study with the dynamic windows approach that selects different weight parameters. The results show that although the average calculation time of fuzzy logic improved dynamic windows approach is slightly longer, the robustness is better, the generated path is shorter, and the energy consumption of the drive motors is lower. The LEO ROS mobile robot is selected for the experiments, the results also show that compared with the dynamic windows approach and the time elastic band, the algorithm proposed in this study has better performance in terms of length and smoothness of paths and robustness. Mobile robot Path planning Dynamic obstacle avoidance Fuzzy logic control method Optimal energy consumption Dynamic window approach Deng, Haigang verfasserin aut Feng, Xianying verfasserin aut Li, Peigang verfasserin aut Li, Yanfei verfasserin aut Liu, Haiyang verfasserin aut Enthalten in Computers & industrial engineering Amsterdam [u.a.] : Elsevier Science, 1976 187 Online-Ressource (DE-627)320606899 (DE-600)2020859-5 (DE-576)259271780 0360-8352 nnns volume:187 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 85.35 Fertigung VZ 54.80 Angewandte Informatik VZ AR 187
spelling	10.1016/j.cie.2023.109767 doi (DE-627)ELV066415950 (ELSEVIER)S0360-8352(23)00791-X DE-627 ger DE-627 rda eng 004 VZ 85.35 bkl 54.80 bkl Yao, Ming verfasserin aut Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The path planning and obstacles avoidance in dynamic environments are vitally important problems for auto-navigation of mobile robots. Generally, the dynamic windows approach is one of the commonly used algorithms to solve the above-mentioned problems. Nevertheless, the robustness of dynamic windows approach is poor, while the generated paths are not smooth. Thus, this paper proposed a fuzzy logic improved dynamic windows approach. Firstly, the energy consumption model of the drive motor is established and used to extend the evaluation function of the dynamic windows approach, which helps to improve the smoothness of generated paths. Secondly, three fuzzy logic controllers are designed based on the directional rules, safety rules and fusion rules respectively to output weight parameters real-time, which improves the robustness. In static and dynamic simulations, maps with sizes of 20 × 20 and 30 × 30 are designed respectively to compare the paths generated by the algorithm proposed in this study with the dynamic windows approach that selects different weight parameters. The results show that although the average calculation time of fuzzy logic improved dynamic windows approach is slightly longer, the robustness is better, the generated path is shorter, and the energy consumption of the drive motors is lower. The LEO ROS mobile robot is selected for the experiments, the results also show that compared with the dynamic windows approach and the time elastic band, the algorithm proposed in this study has better performance in terms of length and smoothness of paths and robustness. Mobile robot Path planning Dynamic obstacle avoidance Fuzzy logic control method Optimal energy consumption Dynamic window approach Deng, Haigang verfasserin aut Feng, Xianying verfasserin aut Li, Peigang verfasserin aut Li, Yanfei verfasserin aut Liu, Haiyang verfasserin aut Enthalten in Computers & industrial engineering Amsterdam [u.a.] : Elsevier Science, 1976 187 Online-Ressource (DE-627)320606899 (DE-600)2020859-5 (DE-576)259271780 0360-8352 nnns volume:187 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 85.35 Fertigung VZ 54.80 Angewandte Informatik VZ AR 187
allfields_unstemmed	10.1016/j.cie.2023.109767 doi (DE-627)ELV066415950 (ELSEVIER)S0360-8352(23)00791-X DE-627 ger DE-627 rda eng 004 VZ 85.35 bkl 54.80 bkl Yao, Ming verfasserin aut Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The path planning and obstacles avoidance in dynamic environments are vitally important problems for auto-navigation of mobile robots. Generally, the dynamic windows approach is one of the commonly used algorithms to solve the above-mentioned problems. Nevertheless, the robustness of dynamic windows approach is poor, while the generated paths are not smooth. Thus, this paper proposed a fuzzy logic improved dynamic windows approach. Firstly, the energy consumption model of the drive motor is established and used to extend the evaluation function of the dynamic windows approach, which helps to improve the smoothness of generated paths. Secondly, three fuzzy logic controllers are designed based on the directional rules, safety rules and fusion rules respectively to output weight parameters real-time, which improves the robustness. In static and dynamic simulations, maps with sizes of 20 × 20 and 30 × 30 are designed respectively to compare the paths generated by the algorithm proposed in this study with the dynamic windows approach that selects different weight parameters. The results show that although the average calculation time of fuzzy logic improved dynamic windows approach is slightly longer, the robustness is better, the generated path is shorter, and the energy consumption of the drive motors is lower. The LEO ROS mobile robot is selected for the experiments, the results also show that compared with the dynamic windows approach and the time elastic band, the algorithm proposed in this study has better performance in terms of length and smoothness of paths and robustness. Mobile robot Path planning Dynamic obstacle avoidance Fuzzy logic control method Optimal energy consumption Dynamic window approach Deng, Haigang verfasserin aut Feng, Xianying verfasserin aut Li, Peigang verfasserin aut Li, Yanfei verfasserin aut Liu, Haiyang verfasserin aut Enthalten in Computers & industrial engineering Amsterdam [u.a.] : Elsevier Science, 1976 187 Online-Ressource (DE-627)320606899 (DE-600)2020859-5 (DE-576)259271780 0360-8352 nnns volume:187 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 85.35 Fertigung VZ 54.80 Angewandte Informatik VZ AR 187
allfieldsGer	10.1016/j.cie.2023.109767 doi (DE-627)ELV066415950 (ELSEVIER)S0360-8352(23)00791-X DE-627 ger DE-627 rda eng 004 VZ 85.35 bkl 54.80 bkl Yao, Ming verfasserin aut Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The path planning and obstacles avoidance in dynamic environments are vitally important problems for auto-navigation of mobile robots. Generally, the dynamic windows approach is one of the commonly used algorithms to solve the above-mentioned problems. Nevertheless, the robustness of dynamic windows approach is poor, while the generated paths are not smooth. Thus, this paper proposed a fuzzy logic improved dynamic windows approach. Firstly, the energy consumption model of the drive motor is established and used to extend the evaluation function of the dynamic windows approach, which helps to improve the smoothness of generated paths. Secondly, three fuzzy logic controllers are designed based on the directional rules, safety rules and fusion rules respectively to output weight parameters real-time, which improves the robustness. In static and dynamic simulations, maps with sizes of 20 × 20 and 30 × 30 are designed respectively to compare the paths generated by the algorithm proposed in this study with the dynamic windows approach that selects different weight parameters. The results show that although the average calculation time of fuzzy logic improved dynamic windows approach is slightly longer, the robustness is better, the generated path is shorter, and the energy consumption of the drive motors is lower. The LEO ROS mobile robot is selected for the experiments, the results also show that compared with the dynamic windows approach and the time elastic band, the algorithm proposed in this study has better performance in terms of length and smoothness of paths and robustness. Mobile robot Path planning Dynamic obstacle avoidance Fuzzy logic control method Optimal energy consumption Dynamic window approach Deng, Haigang verfasserin aut Feng, Xianying verfasserin aut Li, Peigang verfasserin aut Li, Yanfei verfasserin aut Liu, Haiyang verfasserin aut Enthalten in Computers & industrial engineering Amsterdam [u.a.] : Elsevier Science, 1976 187 Online-Ressource (DE-627)320606899 (DE-600)2020859-5 (DE-576)259271780 0360-8352 nnns volume:187 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 85.35 Fertigung VZ 54.80 Angewandte Informatik VZ AR 187
allfieldsSound	10.1016/j.cie.2023.109767 doi (DE-627)ELV066415950 (ELSEVIER)S0360-8352(23)00791-X DE-627 ger DE-627 rda eng 004 VZ 85.35 bkl 54.80 bkl Yao, Ming verfasserin aut Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The path planning and obstacles avoidance in dynamic environments are vitally important problems for auto-navigation of mobile robots. Generally, the dynamic windows approach is one of the commonly used algorithms to solve the above-mentioned problems. Nevertheless, the robustness of dynamic windows approach is poor, while the generated paths are not smooth. Thus, this paper proposed a fuzzy logic improved dynamic windows approach. Firstly, the energy consumption model of the drive motor is established and used to extend the evaluation function of the dynamic windows approach, which helps to improve the smoothness of generated paths. Secondly, three fuzzy logic controllers are designed based on the directional rules, safety rules and fusion rules respectively to output weight parameters real-time, which improves the robustness. In static and dynamic simulations, maps with sizes of 20 × 20 and 30 × 30 are designed respectively to compare the paths generated by the algorithm proposed in this study with the dynamic windows approach that selects different weight parameters. The results show that although the average calculation time of fuzzy logic improved dynamic windows approach is slightly longer, the robustness is better, the generated path is shorter, and the energy consumption of the drive motors is lower. The LEO ROS mobile robot is selected for the experiments, the results also show that compared with the dynamic windows approach and the time elastic band, the algorithm proposed in this study has better performance in terms of length and smoothness of paths and robustness. Mobile robot Path planning Dynamic obstacle avoidance Fuzzy logic control method Optimal energy consumption Dynamic window approach Deng, Haigang verfasserin aut Feng, Xianying verfasserin aut Li, Peigang verfasserin aut Li, Yanfei verfasserin aut Liu, Haiyang verfasserin aut Enthalten in Computers & industrial engineering Amsterdam [u.a.] : Elsevier Science, 1976 187 Online-Ressource (DE-627)320606899 (DE-600)2020859-5 (DE-576)259271780 0360-8352 nnns volume:187 GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 85.35 Fertigung VZ 54.80 Angewandte Informatik VZ AR 187
language	English
source	Enthalten in Computers & industrial engineering 187 volume:187
sourceStr	Enthalten in Computers & industrial engineering 187 volume:187
format_phy_str_mv	Article
bklname	Fertigung Angewandte Informatik
institution	findex.gbv.de
topic_facet	Mobile robot Path planning Dynamic obstacle avoidance Fuzzy logic control method Optimal energy consumption Dynamic window approach
dewey-raw	004
isfreeaccess_bool	false
container_title	Computers & industrial engineering
authorswithroles_txt_mv	Yao, Ming @@aut@@ Deng, Haigang @@aut@@ Feng, Xianying @@aut@@ Li, Peigang @@aut@@ Li, Yanfei @@aut@@ Liu, Haiyang @@aut@@
publishDateDaySort_date	2023-01-01T00:00:00Z
hierarchy_top_id	320606899
dewey-sort	14
id	ELV066415950
language_de	englisch
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Generally, the dynamic windows approach is one of the commonly used algorithms to solve the above-mentioned problems. Nevertheless, the robustness of dynamic windows approach is poor, while the generated paths are not smooth. Thus, this paper proposed a fuzzy logic improved dynamic windows approach. Firstly, the energy consumption model of the drive motor is established and used to extend the evaluation function of the dynamic windows approach, which helps to improve the smoothness of generated paths. Secondly, three fuzzy logic controllers are designed based on the directional rules, safety rules and fusion rules respectively to output weight parameters real-time, which improves the robustness. In static and dynamic simulations, maps with sizes of 20 × 20 and 30 × 30 are designed respectively to compare the paths generated by the algorithm proposed in this study with the dynamic windows approach that selects different weight parameters. 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author	Yao, Ming
spellingShingle	Yao, Ming ddc 004 bkl 85.35 bkl 54.80 misc Mobile robot misc Path planning misc Dynamic obstacle avoidance misc Fuzzy logic control method misc Optimal energy consumption misc Dynamic window approach Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots
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topic_title	004 VZ 85.35 bkl 54.80 bkl Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots Mobile robot Path planning Dynamic obstacle avoidance Fuzzy logic control method Optimal energy consumption Dynamic window approach
topic	ddc 004 bkl 85.35 bkl 54.80 misc Mobile robot misc Path planning misc Dynamic obstacle avoidance misc Fuzzy logic control method misc Optimal energy consumption misc Dynamic window approach
topic_unstemmed	ddc 004 bkl 85.35 bkl 54.80 misc Mobile robot misc Path planning misc Dynamic obstacle avoidance misc Fuzzy logic control method misc Optimal energy consumption misc Dynamic window approach
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title	Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots
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title_full	Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots
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title_sort	improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots
title_auth	Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots
abstract	The path planning and obstacles avoidance in dynamic environments are vitally important problems for auto-navigation of mobile robots. Generally, the dynamic windows approach is one of the commonly used algorithms to solve the above-mentioned problems. Nevertheless, the robustness of dynamic windows approach is poor, while the generated paths are not smooth. Thus, this paper proposed a fuzzy logic improved dynamic windows approach. Firstly, the energy consumption model of the drive motor is established and used to extend the evaluation function of the dynamic windows approach, which helps to improve the smoothness of generated paths. Secondly, three fuzzy logic controllers are designed based on the directional rules, safety rules and fusion rules respectively to output weight parameters real-time, which improves the robustness. In static and dynamic simulations, maps with sizes of 20 × 20 and 30 × 30 are designed respectively to compare the paths generated by the algorithm proposed in this study with the dynamic windows approach that selects different weight parameters. The results show that although the average calculation time of fuzzy logic improved dynamic windows approach is slightly longer, the robustness is better, the generated path is shorter, and the energy consumption of the drive motors is lower. The LEO ROS mobile robot is selected for the experiments, the results also show that compared with the dynamic windows approach and the time elastic band, the algorithm proposed in this study has better performance in terms of length and smoothness of paths and robustness.
abstractGer	The path planning and obstacles avoidance in dynamic environments are vitally important problems for auto-navigation of mobile robots. Generally, the dynamic windows approach is one of the commonly used algorithms to solve the above-mentioned problems. Nevertheless, the robustness of dynamic windows approach is poor, while the generated paths are not smooth. Thus, this paper proposed a fuzzy logic improved dynamic windows approach. Firstly, the energy consumption model of the drive motor is established and used to extend the evaluation function of the dynamic windows approach, which helps to improve the smoothness of generated paths. Secondly, three fuzzy logic controllers are designed based on the directional rules, safety rules and fusion rules respectively to output weight parameters real-time, which improves the robustness. In static and dynamic simulations, maps with sizes of 20 × 20 and 30 × 30 are designed respectively to compare the paths generated by the algorithm proposed in this study with the dynamic windows approach that selects different weight parameters. The results show that although the average calculation time of fuzzy logic improved dynamic windows approach is slightly longer, the robustness is better, the generated path is shorter, and the energy consumption of the drive motors is lower. The LEO ROS mobile robot is selected for the experiments, the results also show that compared with the dynamic windows approach and the time elastic band, the algorithm proposed in this study has better performance in terms of length and smoothness of paths and robustness.
abstract_unstemmed	The path planning and obstacles avoidance in dynamic environments are vitally important problems for auto-navigation of mobile robots. Generally, the dynamic windows approach is one of the commonly used algorithms to solve the above-mentioned problems. Nevertheless, the robustness of dynamic windows approach is poor, while the generated paths are not smooth. Thus, this paper proposed a fuzzy logic improved dynamic windows approach. Firstly, the energy consumption model of the drive motor is established and used to extend the evaluation function of the dynamic windows approach, which helps to improve the smoothness of generated paths. Secondly, three fuzzy logic controllers are designed based on the directional rules, safety rules and fusion rules respectively to output weight parameters real-time, which improves the robustness. In static and dynamic simulations, maps with sizes of 20 × 20 and 30 × 30 are designed respectively to compare the paths generated by the algorithm proposed in this study with the dynamic windows approach that selects different weight parameters. The results show that although the average calculation time of fuzzy logic improved dynamic windows approach is slightly longer, the robustness is better, the generated path is shorter, and the energy consumption of the drive motors is lower. The LEO ROS mobile robot is selected for the experiments, the results also show that compared with the dynamic windows approach and the time elastic band, the algorithm proposed in this study has better performance in terms of length and smoothness of paths and robustness.
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title_short	Improved dynamic windows approach based on energy consumption management and fuzzy logic control for local path planning of mobile robots
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author2	Deng, Haigang Feng, Xianying Li, Peigang Li, Yanfei Liu, Haiyang
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