000153683 001__ 153683 000153683 005__ 20251017144626.0 000153683 0247_ $$2doi$$a10.1109/TRO.2025.3552350 000153683 0248_ $$2sideral$$a143764 000153683 037__ $$aART-2025-143764 000153683 041__ $$aeng 000153683 100__ $$aMartinez-Baselga, Diego$$uUniversidad de Zaragoza 000153683 245__ $$aAVOCADO: Adaptive Optimal Collision Avoidance Driven by Opinion 000153683 260__ $$c2025 000153683 5060_ $$aAccess copy available to the general public$$fUnrestricted 000153683 5203_ $$aWe present AdaptiVe Optimal Collision Avoidance Driven by Opinion (AVOCADO), a novel navigation approach to address holonomic robot collision avoidance when the robot does not know how cooperative the other agents in the environment are. AVOCADO departs from a velocity obstacle's (VO) formulation akin to the optimal reciprocal collision avoidance method. However, instead of assuming reciprocity, it poses an adaptive control problem to adapt to the cooperation level of other robots and agents in real time. This is achieved through a novel nonlinear opinion dynamics design that relies solely on sensor observations. As a by-product, we leverage tools from the opinion dynamics formulation to naturally avoid the deadlocks in geometrically symmetric scenarios that typically suffer VO-based planners. Extensive numerical simulations show that AVOCADO surpasses existing motion planners in mixed cooperative/noncooperative navigation environments in terms of success rate, time to goal and computational time. In addition, we conduct multiple real experiments that verify that AVOCADO is able to avoid collisions in environments crowded with other robots and humans. 000153683 536__ $$9info:eu-repo/grantAgreement/ES/AEI/PID2022-139615OB-I00$$9info:eu-repo/grantAgreement/ES/AEI/PRE2020-094415$$9info:eu-repo/grantAgreement/EUR/AEI/TED2021-130224B-I00$$9info:eu-repo/grantAgreement/ES/DGA/T45-23R$$9info:eu-repo/grantAgreement/ES/MCIU/FPU19-05700$$9info:eu-repo/grantAgreement/ES/MICINN-AEI-FEDER/PID2021-124137OB-I00$$9info:eu-repo/grantAgreement/ES/MICINN/PID2021-125514NB-I00 000153683 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es 000153683 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000153683 700__ $$0(orcid)0000-0001-9671-4056$$aSebastián, Eduardo$$uUniversidad de Zaragoza 000153683 700__ $$0(orcid)0000-0002-5176-3767$$aMontijano, Eduardo$$uUniversidad de Zaragoza 000153683 700__ $$0(orcid)0000-0002-6722-5541$$aRiazuelo, Luis$$uUniversidad de Zaragoza 000153683 700__ $$0(orcid)0000-0002-3032-954X$$aSagüés, Carlos$$uUniversidad de Zaragoza 000153683 700__ $$0(orcid)0000-0002-0449-2300$$aMontano, Luis$$uUniversidad de Zaragoza 000153683 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát. 000153683 773__ $$g41 (2025), 2495-2511$$pIEEE Trans. Robot.$$tIEEE Transactions on Robotics$$x1552-3098 000153683 8564_ $$s11770480$$uhttps://zaguan.unizar.es/record/153683/files/texto_completo.pdf$$yVersión publicada 000153683 8564_ $$s3269303$$uhttps://zaguan.unizar.es/record/153683/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000153683 909CO $$ooai:zaguan.unizar.es:153683$$particulos$$pdriver 000153683 951__ $$a2025-10-17-14:24:25 000153683 980__ $$aARTICLE