{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T05:47:07Z","timestamp":1782539227200,"version":"3.54.5"},"reference-count":27,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T00:00:00Z","timestamp":1782345600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>To address the problem of high-frequency roll disturbances generated during dynamic balancing in non-coaxial two-wheeled robots, this paper proposes a Rotation-Optimized Inertial\u2013Visual SLAM system (ROIV-SLAM) for robust state estimation. The proposed approach adopts a decoupled architecture for translation and rotation estimation. In the front-end, an Extended Kalman Filter (EKF) is employed to fuse LiDAR, an inertial measurement unit (IMU), and wheel odometry to obtain an initial translation estimate. Meanwhile, a physical manifold constraint is constructed using the gravity vector and surface normals extracted from RGB-D point clouds, supporting stable rotation estimation under high-frequency disturbances through Lie-group-based optimization. In the back-end, a factor graph is established, and loop closure robustness is enhanced through vision\u2013LiDAR scan matching. Experimental results indicate that ROIV-SLAM achieves improved trajectory consistency with respect to the optimized reference trajectory and more robust mapping performance compared with the evaluated baseline approaches in the tested scenarios. The results further suggest that introducing task-specific physical dynamic constraints and a decoupled estimation mechanism helps suppress high-frequency motion noise inherent to balancing robots, thereby improving the robustness of state estimation in complex environments.<\/jats:p>","DOI":"10.3390\/s26134053","type":"journal-article","created":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T00:49:23Z","timestamp":1782434963000},"page":"4053","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["ROIV-SLAM: Rotation-Optimized Inertial\u2013Visual SLAM for a Non-Coaxial Two-Wheeled Robot Under Roll Disturbances"],"prefix":"10.3390","volume":"26","author":[{"given":"Chong","family":"Feng","sequence":"first","affiliation":[{"name":"College of Information and Communication, Dalian Minzu University, Dalian 116600, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Ren","sequence":"additional","affiliation":[{"name":"College of Information and Communication, Dalian Minzu University, Dalian 116600, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenbo","family":"Gao","sequence":"additional","affiliation":[{"name":"College of Information and Communication, Dalian Minzu University, Dalian 116600, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhan","family":"Shi","sequence":"additional","affiliation":[{"name":"College of Information and Communication, Dalian Minzu University, Dalian 116600, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chunjuan","family":"Bo","sequence":"additional","affiliation":[{"name":"College of Information and Communication, Dalian Minzu University, Dalian 116600, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chang","family":"Kou","sequence":"additional","affiliation":[{"name":"Dalian Everyday Good Electronic Co., Ltd., Tieshan Dongsan Road, Dalian 116630, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhun","family":"Feng","sequence":"additional","affiliation":[{"name":"Industry\u2013Education Integration Center, Liaoning Railway Vocational and Technical College, Jinzhou 121000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Shan, T., Englot, B., Meyers, D., Wang, W., Ratti, C., and Rus, D. 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