{"id":"https://openalex.org/W4416748041","doi":"https://doi.org/10.1109/iros60139.2025.11247719","title":"Context-Aware Behavior Learning with Heuristic Motion Memory for Underwater Manipulation","display_name":"Context-Aware Behavior Learning with Heuristic Motion Memory for Underwater Manipulation","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416748041","doi":"https://doi.org/10.1109/iros60139.2025.11247719"},"language":null,"primary_location":{"id":"doi:10.1109/iros60139.2025.11247719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11247719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110749337","display_name":"M. Buchholz","orcid":null},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Markus Buchholz","raw_affiliation_strings":["Heriot-Watt University,School of Engineering & Physical Sciences,Edinburgh,UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heriot-Watt University,School of Engineering & Physical Sciences,Edinburgh,UK","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088668090","display_name":"Ignacio Carlucho","orcid":"https://orcid.org/0000-0002-6262-480X"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ignacio Carlucho","raw_affiliation_strings":["Heriot-Watt University,School of Engineering & Physical Sciences,Edinburgh,UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heriot-Watt University,School of Engineering & Physical Sciences,Edinburgh,UK","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020277400","display_name":"Michele Grimaldi","orcid":"https://orcid.org/0000-0001-8284-6998"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Michele Grimaldi","raw_affiliation_strings":["Heriot-Watt University,School of Engineering & Physical Sciences,Edinburgh,UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heriot-Watt University,School of Engineering & Physical Sciences,Edinburgh,UK","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046746682","display_name":"Maria Koskinopoulou","orcid":"https://orcid.org/0000-0002-8040-2995"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Maria Koskinopoulou","raw_affiliation_strings":["Heriot-Watt University,School of Engineering & Physical Sciences,Edinburgh,UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heriot-Watt University,School of Engineering & Physical Sciences,Edinburgh,UK","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034972272","display_name":"Yvan P\u00e9tillot","orcid":"https://orcid.org/0000-0002-1596-289X"},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yvan R. Petillot","raw_affiliation_strings":["Heriot-Watt University,School of Engineering & Physical Sciences,Edinburgh,UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heriot-Watt University,School of Engineering & Physical Sciences,Edinburgh,UK","institution_ids":["https://openalex.org/I32062511"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32468481,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"20154","last_page":"20161"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10586","display_name":"Robotic Path Planning Algorithms","score":0.5407000184059143,"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":0.5407000184059143,"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/T11192","display_name":"Underwater Vehicles and Communication Systems","score":0.3353999853134155,"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"}},{"id":"https://openalex.org/T11622","display_name":"Maritime Navigation and Safety","score":0.027699999511241913,"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/motion-planning","display_name":"Motion planning","score":0.7580000162124634},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6039999723434448},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5867000222206116},{"id":"https://openalex.org/keywords/underwater","display_name":"Underwater","score":0.4896000027656555},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.3488999903202057},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.3481999933719635},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.34610000252723694},{"id":"https://openalex.org/keywords/dynamic-bayesian-network","display_name":"Dynamic Bayesian network","score":0.3449000120162964}],"concepts":[{"id":"https://openalex.org/C81074085","wikidata":"https://www.wikidata.org/wiki/Q366872","display_name":"Motion planning","level":3,"score":0.7580000162124634},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6956999897956848},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6039999723434448},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5867000222206116},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49900001287460327},{"id":"https://openalex.org/C98083399","wikidata":"https://www.wikidata.org/wiki/Q3246517","display_name":"Underwater","level":2,"score":0.4896000027656555},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37720000743865967},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.3488999903202057},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.3481999933719635},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.34610000252723694},{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.3449000120162964},{"id":"https://openalex.org/C2776999362","wikidata":"https://www.wikidata.org/wiki/Q2349274","display_name":"Planner","level":2,"score":0.334199994802475},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3147999942302704},{"id":"https://openalex.org/C17098449","wikidata":"https://www.wikidata.org/wiki/Q176814","display_name":"Partially observable Markov decision process","level":4,"score":0.3082999885082245},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.3075000047683716},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.27059999108314514},{"id":"https://openalex.org/C2778803389","wikidata":"https://www.wikidata.org/wiki/Q7246866","display_name":"Probabilistic roadmap","level":4,"score":0.2597000002861023},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.25200000405311584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros60139.2025.11247719","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros60139.2025.11247719","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2099893201","https://openalex.org/W2128990851","https://openalex.org/W2145778183","https://openalex.org/W3006593729","https://openalex.org/W3091401032","https://openalex.org/W3108001770","https://openalex.org/W4200224433","https://openalex.org/W4226310289","https://openalex.org/W4285102430","https://openalex.org/W4288726593","https://openalex.org/W4293232200","https://openalex.org/W4366697952","https://openalex.org/W4378530298","https://openalex.org/W4382365724","https://openalex.org/W4383897618","https://openalex.org/W4386169345","https://openalex.org/W4392337719","https://openalex.org/W4400111497","https://openalex.org/W4401415533","https://openalex.org/W4401541088","https://openalex.org/W4402990942","https://openalex.org/W4403123342","https://openalex.org/W4404577250","https://openalex.org/W4404652056","https://openalex.org/W4404982834"],"related_works":[],"abstract_inverted_index":{"Autonomous":[0],"motion":[1,16,25,59,172],"planning":[2,17,60,111,173],"is":[3],"critical":[4],"for":[5,61,86],"efficient":[6],"and":[7,27,91,108,127,141,157],"safe":[8],"underwater":[9,34,168],"manipulation":[10],"in":[11,33,152,174],"dynamic":[12,178],"marine":[13,179],"environments.":[14],"Current":[15],"methods":[18],"often":[19],"fail":[20],"to":[21,29,57,75,117],"effectively":[22],"utilize":[23],"prior":[24],"experiences":[26],"adapt":[28],"real-time":[30,110,124],"uncertainties":[31],"inherent":[32],"settings.":[35],"In":[36],"this":[37],"paper,":[38],"we":[39,145],"introduce":[40],"an":[41],"Adaptive":[42],"Heuristic":[43,50],"Motion":[44,51],"Planner":[45],"framework":[46,98],"that":[47,84],"integrates":[48],"a":[49,80],"Space":[52],"(HMS)":[53],"with":[54],"Bayesian":[55,113],"Networks":[56,114],"enhance":[58],"autonomous":[62,167],"under-water":[63],"manipulation.":[64],"Our":[65],"approach":[66,161],"employs":[67],"the":[68,101,132,147,164,175],"Probabilistic":[69],"Roadmap":[70],"(PRM)":[71],"algorithm":[72],"within":[73],"HMS":[74],"optimize":[76],"paths":[77],"by":[78],"minimizing":[79],"composite":[81],"cost":[82],"function":[83],"accounts":[85],"distance,":[87],"uncertainty,":[88],"energy":[89],"consumption,":[90],"execution":[92],"time.":[93],"By":[94],"leveraging":[95],"HMS,":[96],"our":[97,150],"significantly":[99,162],"reduces":[100],"search":[102],"space,":[103],"thereby":[104,130],"boosting":[105],"computational":[106],"performance":[107,156],"enabling":[109],"capabilities.":[112],"are":[115],"utilized":[116],"dynamically":[118],"update":[119],"uncertainty":[120],"estimates":[121],"based":[122],"on":[123],"sensor":[125],"data":[126],"environmental":[128],"conditions,":[129],"refining":[131],"joint":[133],"probability":[134],"of":[135,149,154,166,177],"path":[136],"success.":[137],"Through":[138],"extensive":[139],"simulations":[140],"real-world":[142],"test":[143],"scenarios,":[144],"showcase":[146],"advantages":[148],"method":[151],"terms":[153],"enhanced":[155],"robustness.":[158],"This":[159],"probabilistic":[160],"advances":[163],"capability":[165],"robots,":[169],"ensuring":[170],"optimized":[171],"face":[176],"challenges.":[180]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-28T00:00:00"}