Optimal path planning for intelligent automated wheelchair using DDSRPSO
PurposeThis paper aims to find the optimal path using directionally driven self-regulating particle swarm optimization (DDSRPSO) with high accuracy and minimal response time.Design/methodology/approachThis paper encompasses optimal path planning for automated wheelchair design using swarm intelligen...
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| Veröffentlicht in: | International Journal of Pervasive Computing and Communications 2021-02, Vol.17 (1), p.109-120 |
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| container_title | International Journal of Pervasive Computing and Communications |
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| creator | Thirugnanasambandam, Kalaipriyan R.S., Raghav Loganathan, Jayakumar Dumka, Ankur V., Dhilipkumar |
| description | PurposeThis paper aims to find the optimal path using directionally driven self-regulating particle swarm optimization (DDSRPSO) with high accuracy and minimal response time.Design/methodology/approachThis paper encompasses optimal path planning for automated wheelchair design using swarm intelligence algorithm DDSRPSO. Swarm intelligence is incorporated in optimization due to the cooperative behavior in it.FindingsThe proposed work has been evaluated in three different regions and the comparison has been made with particle swarm optimization and self-regulating particle swarm optimization and proved that the optimal path with robustness is from the proposed algorithm.Originality/valueThe performance metrics used for evaluation includes computational time, success rate and distance traveled. |
| doi_str_mv | 10.1108/IJPCC-05-2020-0033 |
| format | Article |
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Swarm intelligence is incorporated in optimization due to the cooperative behavior in it.FindingsThe proposed work has been evaluated in three different regions and the comparison has been made with particle swarm optimization and self-regulating particle swarm optimization and proved that the optimal path with robustness is from the proposed algorithm.Originality/valueThe performance metrics used for evaluation includes computational time, success rate and distance traveled.</description><subject>Algorithms</subject><subject>Automation</subject><subject>Computing time</subject><subject>Design</subject><subject>Optimization</subject><subject>Particle swarm optimization</subject><subject>Path planning</subject><subject>Performance evaluation</subject><subject>Performance measurement</subject><subject>Planning</subject><subject>Response time</subject><subject>Robots</subject><subject>Sensors</subject><subject>Swarm intelligence</subject><subject>Velocity</subject><subject>Wheelchairs</subject><issn>1742-7371</issn><issn>1742-738X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNo9kF1LwzAUhoMoOKd_wKuA19F8N7uUTrfJYMMpeBeyNNk6urYmKeK_t3XizTnn4uE9vA8AtwTfE4LVw-JlnecIC0QxxQhjxs7AiGScooypj_P_OyOX4CrGA8ZSMaJGYL5qU3k0FWxN2sO2MnVd1jvomwDLOrmqKneuTtB0qTma5Ar4tXeusntTBtjFAZ1ON6_rzeoaXHhTRXfzt8fg_fnpLZ-j5Wq2yB-XyDKSJSScYYQXQlnJuZDKe-GlILLYUuYV3rJCUcWEV5b3o5DWSSuInxR9AWG3io3B3Sm3Dc1n52LSh6YLdf9SU8E4nkhOeU_RE2VDE2NwXrehrxm-NcF6MKZ_jWks9GBMD8bYD32oXjs</recordid><startdate>20210219</startdate><enddate>20210219</enddate><creator>Thirugnanasambandam, Kalaipriyan</creator><creator>R.S., Raghav</creator><creator>Loganathan, Jayakumar</creator><creator>Dumka, Ankur</creator><creator>V., Dhilipkumar</creator><general>Emerald Group Publishing Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7XB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>20210219</creationdate><title>Optimal path planning for intelligent automated wheelchair using DDSRPSO</title><author>Thirugnanasambandam, Kalaipriyan ; R.S., Raghav ; Loganathan, Jayakumar ; Dumka, Ankur ; V., Dhilipkumar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c317t-5ea314d58c644568ff5f6516db23f80b3d82835f8c45f8d6ce6c51f9d1745cb83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algorithms</topic><topic>Automation</topic><topic>Computing time</topic><topic>Design</topic><topic>Optimization</topic><topic>Particle swarm optimization</topic><topic>Path planning</topic><topic>Performance evaluation</topic><topic>Performance measurement</topic><topic>Planning</topic><topic>Response time</topic><topic>Robots</topic><topic>Sensors</topic><topic>Swarm intelligence</topic><topic>Velocity</topic><topic>Wheelchairs</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Thirugnanasambandam, Kalaipriyan</creatorcontrib><creatorcontrib>R.S., Raghav</creatorcontrib><creatorcontrib>Loganathan, Jayakumar</creatorcontrib><creatorcontrib>Dumka, Ankur</creatorcontrib><creatorcontrib>V., Dhilipkumar</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>International Journal of Pervasive Computing and Communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Thirugnanasambandam, Kalaipriyan</au><au>R.S., Raghav</au><au>Loganathan, Jayakumar</au><au>Dumka, Ankur</au><au>V., Dhilipkumar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimal path planning for intelligent automated wheelchair using DDSRPSO</atitle><jtitle>International Journal of Pervasive Computing and Communications</jtitle><date>2021-02-19</date><risdate>2021</risdate><volume>17</volume><issue>1</issue><spage>109</spage><epage>120</epage><pages>109-120</pages><issn>1742-7371</issn><eissn>1742-738X</eissn><abstract>PurposeThis paper aims to find the optimal path using directionally driven self-regulating particle swarm optimization (DDSRPSO) with high accuracy and minimal response time.Design/methodology/approachThis paper encompasses optimal path planning for automated wheelchair design using swarm intelligence algorithm DDSRPSO. Swarm intelligence is incorporated in optimization due to the cooperative behavior in it.FindingsThe proposed work has been evaluated in three different regions and the comparison has been made with particle swarm optimization and self-regulating particle swarm optimization and proved that the optimal path with robustness is from the proposed algorithm.Originality/valueThe performance metrics used for evaluation includes computational time, success rate and distance traveled.</abstract><cop>Bingley</cop><pub>Emerald Group Publishing Limited</pub><doi>10.1108/IJPCC-05-2020-0033</doi><tpages>12</tpages></addata></record> |
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| ispartof | International Journal of Pervasive Computing and Communications, 2021-02, Vol.17 (1), p.109-120 |
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| language | eng |
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| source | Emerald Journals; Standard: Emerald eJournal Premier Collection |
| subjects | Algorithms Automation Computing time Design Optimization Particle swarm optimization Path planning Performance evaluation Performance measurement Planning Response time Robots Sensors Swarm intelligence Velocity Wheelchairs |
| title | Optimal path planning for intelligent automated wheelchair using DDSRPSO |
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