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Being an effective strategy, while caging configuration-based manipulation frameworks have successfully provided robust solutions, they are not broadly applicable due to their strict requirements on the availability of multiple robots, widely distributed contacts, or specific geometries of robots or objects. Building upon previous sensorless manipulation ideas and uncertainty handling approaches, this work proposes a novel framework termed\n                    <jats:italic toggle=\"yes\">Caging in Time<\/jats:italic>\n                    to allow caging configurations to be formed even with one robot engaged in a task. This concept leverages the insight that while caging requires constraining the object\u2019s motion, only part of the cage actively contacts the object at any moment. As such, by strategically switching the end-effector configuration and collapsing it\n                    <jats:italic toggle=\"yes\">in time<\/jats:italic>\n                    , we form a cage with its necessary portion active whenever needed. We instantiate our approach on challenging quasi-static and dynamic manipulation tasks, showing that\n                    <jats:italic toggle=\"yes\">Caging in Time<\/jats:italic>\n                    can be achieved in general cage formulations including geometry-based and energy-based cages. With extensive experiments, we show robust and accurate manipulation, in an open-loop manner, without requiring detailed knowledge of the object geometry or physical properties, or real-time accurate feedback on the manipulation states. In addition to being an effective and robust open-loop manipulation solution,\n                    <jats:italic toggle=\"yes\">Caging in Time<\/jats:italic>\n                    can be a supplementary strategy to other manipulation systems affected by uncertain or limited robot perception.\n                  <\/jats:p>","DOI":"10.1177\/02783649251343926","type":"journal-article","created":{"date-parts":[[2025,6,10]],"date-time":"2025-06-10T15:32:21Z","timestamp":1749569541000},"page":"2365-2389","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Caging in time: A framework for robust object manipulation under uncertainties and limited robot perception"],"prefix":"10.1177","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-6189-3873","authenticated-orcid":false,"given":"Gaotian","family":"Wang","sequence":"first","affiliation":[{"name":"Rice University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6970-2268","authenticated-orcid":false,"given":"Kejia","family":"Ren","sequence":"additional","affiliation":[{"name":"Rice University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andrew S.","family":"Morgan","sequence":"additional","affiliation":[{"name":"Robotics and AI Institute"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4132-1217","authenticated-orcid":false,"given":"Kaiyu","family":"Hang","sequence":"additional","affiliation":[{"name":"Rice University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,6,10]]},"reference":[{"key":"e_1_3_4_2_1","unstructured":"Akella S Mason MT (1992) Posing polygonal objects in the plane by pushing."},{"key":"e_1_3_4_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.1998.677033"},{"key":"e_1_3_4_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.1997.619318"},{"key":"e_1_3_4_5_1","unstructured":"Althoff M (2010) Reachability analysis and its application to the safety assessment of autonomous cars."},{"key":"e_1_3_4_6_1","doi-asserted-by":"publisher","DOI":"10.23919\/ECC.2019.8796030"},{"key":"e_1_3_4_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2021.09.173"},{"key":"e_1_3_4_8_1","doi-asserted-by":"publisher","DOI":"10.1177\/0278364919887447"},{"key":"e_1_3_4_9_1","doi-asserted-by":"publisher","DOI":"10.15607\/RSS.2021.XVII.089"},{"key":"e_1_3_4_10_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.aat8414"},{"key":"e_1_3_4_11_1","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.abd2666"},{"key":"e_1_3_4_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2017.2721939"},{"key":"e_1_3_4_13_1","doi-asserted-by":"publisher","DOI":"10.1007\/s004539910019"},{"key":"e_1_3_4_14_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-control-053018-023735"},{"key":"e_1_3_4_15_1","doi-asserted-by":"publisher","DOI":"10.1177\/0278364919880257"},{"key":"e_1_3_4_16_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA57147.2024.10611593"},{"key":"e_1_3_4_17_1","unstructured":"Dong Y Cheng X Friedl W et al. 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