{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T10:09:28Z","timestamp":1777716568551,"version":"3.51.4"},"reference-count":83,"publisher":"SAGE Publications","issue":"1-3","license":[{"start":{"date-parts":[[2015,8,21]],"date-time":"2015-08-21T00:00:00Z","timestamp":1440115200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["The International Journal of Robotics Research"],"published-print":{"date-parts":[[2016,1]]},"abstract":"<jats:p>We consider the problem of using real-time feedback from contact sensors to create closed-loop pushing actions. To do so, we formulate the problem as a partially observable Markov decision process (POMDP) with a transition model based on a physics simulator and a reward function that drives the robot towards a successful grasp. We demonstrate that it is intractable to solve the full POMDP with traditional techniques and introduce a novel decomposition of the policy into pre- and post-contact stages to reduce the computational complexity.<\/jats:p>\n                  <jats:p>Our method uses an offline point-based solver on a variable-resolution discretization of the state space to solve for a post-contact policy as a pre-computation step. Then, at runtime, we use an A* search to compute a pre-contact trajectory. We prove that the value of the resulting policy is within a bound of the value of the optimal policy and give intuition about when it performs well. Additionally, we show the policy produced by our algorithm achieves a successful grasp more quickly and with higher probability than a baseline QMDP policy on two different objects in simulation. Finally, we validate our simulation results on a real robot using commercially available tactile sensors.<\/jats:p>","DOI":"10.1177\/0278364915594474","type":"journal-article","created":{"date-parts":[[2015,8,21]],"date-time":"2015-08-21T21:50:24Z","timestamp":1440193824000},"page":"244-264","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":37,"title":["Pre- and post-contact policy decomposition for planar contact manipulation under uncertainty"],"prefix":"10.1177","volume":"35","author":[{"given":"Michael C.","family":"Koval","sequence":"first","affiliation":[{"name":"The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nancy S.","family":"Pollard","sequence":"additional","affiliation":[{"name":"The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, 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