{"id":"https://openalex.org/W7167585681","doi":"https://doi.org/10.1515/comp-2025-0057","title":"Fusion of DWA algorithm and improved Bi RRT obstacle avoidance path planning method in dynamic obstacle environments","display_name":"Fusion of DWA algorithm and improved Bi RRT obstacle avoidance path planning method in dynamic obstacle environments","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7167585681","doi":"https://doi.org/10.1515/comp-2025-0057"},"language":"en","primary_location":{"id":"doi:10.1515/comp-2025-0057","is_oa":true,"landing_page_url":"https://doi.org/10.1515/comp-2025-0057","pdf_url":null,"source":{"id":"https://openalex.org/S4210177004","display_name":"Open Computer Science","issn_l":"2299-1093","issn":["2299-1093"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310313990","host_organization_name":"De Gruyter","host_organization_lineage":["https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Open Computer Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1515/comp-2025-0057","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020052802","display_name":"Yange Li","orcid":"https://orcid.org/0000-0002-8558-0598"},"institutions":[{"id":"https://openalex.org/I37417134","display_name":"Palestine Polytechnic University","ror":"https://ror.org/03wwspn40","country_code":"PS","type":"education","lineage":["https://openalex.org/I37417134"]}],"countries":["PS"],"is_corresponding":true,"raw_author_name":"Yange Li","raw_affiliation_strings":["School of Data Science, Hebi Polytechnic , Hebi 458030 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Data Science, Hebi Polytechnic , Hebi 458030 , China","institution_ids":["https://openalex.org/I37417134"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5020052802"],"corresponding_institution_ids":["https://openalex.org/I37417134"],"apc_list":{"value":1050,"currency":"EUR","value_usd":1187},"apc_paid":{"value":1050,"currency":"EUR","value_usd":1187},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.69230389,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9703999757766724,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.9703999757766724,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11082","display_name":"Spacecraft Dynamics and Control","score":0.002199999988079071,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11622","display_name":"Maritime Navigation and Safety","score":0.00139999995008111,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/obstacle","display_name":"Obstacle","score":0.756600022315979},{"id":"https://openalex.org/keywords/obstacle-avoidance","display_name":"Obstacle avoidance","score":0.7378000020980835},{"id":"https://openalex.org/keywords/motion-planning","display_name":"Motion planning","score":0.7050999999046326},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.6061999797821045},{"id":"https://openalex.org/keywords/dynamic-balance","display_name":"Dynamic balance","score":0.4388999938964844},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.4336000084877014},{"id":"https://openalex.org/keywords/collision-avoidance","display_name":"Collision avoidance","score":0.41440001130104065},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.3873000144958496}],"concepts":[{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.756600022315979},{"id":"https://openalex.org/C6683253","wikidata":"https://www.wikidata.org/wiki/Q7075535","display_name":"Obstacle avoidance","level":4,"score":0.7378000020980835},{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.7050999999046326},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.645799994468689},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.6061999797821045},{"id":"https://openalex.org/C166151169","wikidata":"https://www.wikidata.org/wiki/Q16946937","display_name":"Dynamic balance","level":2,"score":0.4388999938964844},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.4336000084877014},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.42320001125335693},{"id":"https://openalex.org/C2780864053","wikidata":"https://www.wikidata.org/wiki/Q5147495","display_name":"Collision avoidance","level":3,"score":0.41440001130104065},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4034999907016754},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.3873000144958496},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.36719998717308044},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.34389999508857727},{"id":"https://openalex.org/C2776839635","wikidata":"https://www.wikidata.org/wiki/Q14942679","display_name":"Random tree","level":4,"score":0.33340001106262207},{"id":"https://openalex.org/C141934464","wikidata":"https://www.wikidata.org/wiki/Q3305386","display_name":"Local optimum","level":2,"score":0.3197999894618988},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.30410000681877136},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.29589998722076416},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.2955999970436096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2953000068664551},{"id":"https://openalex.org/C158485040","wikidata":"https://www.wikidata.org/wiki/Q4778119","display_name":"Any-angle path planning","level":4,"score":0.2856000065803528},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.27950000762939453},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2754000127315521},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.27219998836517334},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.2549999952316284}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1515/comp-2025-0057","is_oa":true,"landing_page_url":"https://doi.org/10.1515/comp-2025-0057","pdf_url":null,"source":{"id":"https://openalex.org/S4210177004","display_name":"Open Computer Science","issn_l":"2299-1093","issn":["2299-1093"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310313990","host_organization_name":"De Gruyter","host_organization_lineage":["https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Open Computer Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:852536671c2749edb3d7f8ba48352b10","is_oa":false,"landing_page_url":"https://doaj.org/article/852536671c2749edb3d7f8ba48352b10","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Open Computer Science, Vol 16, Iss 1, Pp 390-399 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1515/comp-2025-0057","is_oa":true,"landing_page_url":"https://doi.org/10.1515/comp-2025-0057","pdf_url":null,"source":{"id":"https://openalex.org/S4210177004","display_name":"Open Computer Science","issn_l":"2299-1093","issn":["2299-1093"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310313990","host_organization_name":"De Gruyter","host_organization_lineage":["https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Open Computer Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W3180973535","https://openalex.org/W4291237241","https://openalex.org/W4320168225","https://openalex.org/W4385521685","https://openalex.org/W4386164520","https://openalex.org/W4387060568","https://openalex.org/W4387118767","https://openalex.org/W4392451164","https://openalex.org/W4399485206","https://openalex.org/W4400488003","https://openalex.org/W4401634079","https://openalex.org/W4401969036","https://openalex.org/W4402650624","https://openalex.org/W4402769973","https://openalex.org/W4403600674","https://openalex.org/W4406302499"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"Aiming":[1],"at":[2],"the":[3,61,85,98,102,116,121,126,136,141,159,170,210,219],"problem":[4],"that":[5,177,194],"path":[6,25,133,174,180,238],"planning":[7,26,175],"in":[8,60,97,205],"dynamic":[9,41,52,67,93,184,207],"obstacle":[10,53,68,74,86,94,165,185],"environments":[11],"is":[12,28,47,70],"difficult":[13],"to":[14,72,83,124,139,149],"balance":[15],"global":[16,132,179],"optimality":[17],"and":[18,40,56,66,78,110,128,152,157,161,182,202,209,213,235],"local":[19,164,183,200],"real-time":[20,160,233],"performance,":[21],"a":[22,146,173],"collision":[23,203],"avoidance":[24,186],"method":[27,43,46,196],"proposed":[29],"by":[30],"integrating":[31],"improved":[32,103],"bidirectional":[33,111],"fast":[34],"expanding":[35],"random":[36],"tree":[37],"(Bi":[38],"RRT)":[39],"window":[42],"(DWA).":[44],"This":[45],"divided":[48],"into":[49],"two":[50,171],"stages:":[51],"space":[54,148],"reconstruction":[55,63,75,211],"algorithm":[57,99,106,138],"fusion.":[58],"Firstly,":[59],"spatial":[62],"stage,":[64,101],"static":[65],"information":[69,87],"collected":[71],"construct":[73],"reference":[76],"points,":[77,88],"configuration":[79],"functions":[80],"are":[81,215],"used":[82],"reconstruct":[84],"achieving":[89],"accurate":[90],"modeling":[91],"of":[92,120,131,163,169,221,237],"environments.":[95],"Secondly,":[96],"fusion":[100,168],"Bi":[104],"RRT":[105],"introduces":[107],"greedy":[108],"expansion":[109],"adaptive":[112],"strategies,":[113],"combined":[114],"with":[115,218],"cost":[117],"evaluation":[118,142],"mechanism":[119,176],"A*":[122],"algorithm,":[123],"improve":[125,158],"efficiency":[127],"goal":[129],"orientation":[130],"search;":[134],"Improve":[135],"DWA":[137],"optimize":[140],"function,":[143],"set":[144],"up":[145],"threat":[147],"screen":[150],"obstacles":[151],"enhance":[153],"target":[154],"navigation":[155],"capabilities,":[156],"accuracy":[162],"avoidance.":[166],"The":[167,190,223],"forms":[172],"combines":[178],"guidance":[181],"for":[187],"collaborative":[188],"optimization.":[189],"experimental":[191],"results":[192],"show":[193],"this":[195],"can":[197,227],"effectively":[198],"avoid":[199],"optima":[201],"problems":[204],"complex":[206],"environments,":[208],"position":[212],"width":[214],"dynamically":[216],"adjusted":[217],"movement":[220],"obstacles.":[222],"shortest":[224],"running":[225],"time":[226],"reach":[228],"0.247":[229],"s,":[230],"significantly":[231],"improving":[232],"performance":[234],"adaptability":[236],"planning.":[239]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2026-07-08T00:00:00"}