{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T01:22:33Z","timestamp":1773451353190,"version":"3.50.1"},"reference-count":34,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,5]]},"DOI":"10.1109\/icra.2018.8460730","type":"proceedings-article","created":{"date-parts":[[2018,9,21]],"date-time":"2018-09-21T22:28:03Z","timestamp":1537568883000},"page":"7087-7094","source":"Crossref","is-referenced-by-count":273,"title":["Learning Sampling Distributions for Robot Motion Planning"],"prefix":"10.1109","author":[{"given":"Brian","family":"Ichter","sequence":"first","affiliation":[]},{"given":"James","family":"Harrison","sequence":"additional","affiliation":[]},{"given":"Marco","family":"Pavone","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2014.12.006"},{"key":"ref32","article-title":"Multimodal probabilistic model-based planning for human-robot interaction","author":"schmerling","year":"2018","journal-title":"IEEE ICRA"},{"key":"ref31","article-title":"Using motion primitives in probabilistic sample-based planning for humanoid robots","author":"hauser","year":"2008","journal-title":"WAFR"},{"key":"ref30","article-title":"Dynamic walking and whole-body motion planning for humanoid robots: an integrated approach","author":"dalibard","year":"2013","journal-title":"IJRR"},{"key":"ref34","article-title":"Path planning under kinematic constraints by rapidly exploring manifolds","author":"jaillet","year":"2013","journal-title":"IEEE TRO"},{"key":"ref10","article-title":"A robot path planning framework that learns from experience","author":"berenson","year":"2012","journal-title":"IEEE ICRA"},{"key":"ref11","article-title":"Experience-based planning with sparse roadmap spanners","author":"coleman","year":"2015","journal-title":"IEEE ICRA"},{"key":"ref12","article-title":"Learning approximate cost-to-go metrics to improve sampling-based motion planning","author":"li","year":"2011","journal-title":"IEEE ICRA"},{"key":"ref13","article-title":"Non-parametric learning for natural plan generation","author":"baldwin","year":"2010","journal-title":"IEEE IROS"},{"key":"ref14","article-title":"Demonstration-guided motion planning","author":"ye","year":"2015","journal-title":"ISRR"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"key":"ref16","article-title":"End-to-end training of deep visuomotor policies","author":"levine","year":"2016","journal-title":"JMLR"},{"key":"ref17","article-title":"Motion synthesis through randomized exploration on submanifolds of configuration space","author":"havoutis","year":"2009","journal-title":"Robot Soccer World Cup"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273527"},{"key":"ref19","article-title":"Dynamic movement primitives in latent space of time-dependent variational autoencoders","author":"chen","year":"2016","journal-title":"IEEE-RAS HUMANOIDS"},{"key":"ref28","article-title":"Hybrid PRM sampling with a cost-sensitive adaptive strategy","author":"hsu","year":"2005","journal-title":"IEEE ICRA"},{"key":"ref4","article-title":"Workspace importance sampling for probabilistic roadmap planning","author":"kurniawati","year":"2004","journal-title":"IEEE IROS"},{"key":"ref27","author":"doersch","year":"2016","journal-title":"Tutorial on variational autoencoders"},{"key":"ref3","article-title":"Batch Informed Trees (BIT*): Sampling-based optimal planning via the heuristically guided search of implicit random geometric graphs","author":"gammell","year":"2015","journal-title":"IEEE ICRA"},{"key":"ref6","article-title":"Adapting the sampling distribution in PRM planners based on an approximated medial axis","author":"yang","year":"2004","journal-title":"IEEE ICRA"},{"key":"ref29","author":"schulman","year":"2017","journal-title":"Proximal policy optimization algorithms"},{"key":"ref5","article-title":"Using workspace information as a guide to non-uniform sampling in probabilistic roadmap planners","author":"van","year":"2005","journal-title":"IJRR"},{"key":"ref8","doi-asserted-by":"crossref","DOI":"10.15607\/RSS.2005.I.015","article-title":"Toward optimal configuration space sampling","author":"burns","year":"2005","journal-title":"RSS"},{"key":"ref7","article-title":"Sampling techniques for probabilistic roadmap planners","author":"geraerts","year":"2004","journal-title":"IAS"},{"key":"ref2","article-title":"On the probabilistic foundations of probabilistic roadmap planning","author":"hsu","year":"2006","journal-title":"IJRR"},{"key":"ref9","article-title":"Adaptive workspace biasing for sampling-based planners","author":"zucker","year":"2008","journal-title":"IEEE ICRA"},{"key":"ref1","article-title":"Learning structured output representation using deep conditional generative models","author":"sohn","year":"2015","journal-title":"NIPS"},{"key":"ref20","article-title":"Optimal sampling-based motion planning under differential constraints: the driftless case","author":"schmerling","year":"2015","journal-title":"IEEE ICRA"},{"key":"ref22","article-title":"Sampling-based algorithms for optimal motion planning","author":"karaman","year":"2011","journal-title":"IJRR"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511546877"},{"key":"ref24","article-title":"Deterministic sampling-based motion planning: Optimality, complexity, and performance","author":"janson","year":"2018","journal-title":"IJRR"},{"key":"ref23","article-title":"Fast Marching Tree: A fast marching sampling-based method for optimal motion planning in many dimensions","author":"janson","year":"2015","journal-title":"IJRR"},{"key":"ref26","article-title":"Group Marching Tree: Sampling-based approximately optimal motion planning on GPUs","author":"ichter","year":"2017","journal-title":"IEEE IRC"},{"key":"ref25","author":"kingma","year":"2013","journal-title":"Auto-encoding variational bayes"}],"event":{"name":"2018 IEEE International Conference on Robotics and Automation (ICRA)","location":"Brisbane, QLD","start":{"date-parts":[[2018,5,21]]},"end":{"date-parts":[[2018,5,25]]}},"container-title":["2018 IEEE International Conference on Robotics and Automation (ICRA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8449910\/8460178\/08460730.pdf?arnumber=8460730","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,24]],"date-time":"2020-08-24T00:41:55Z","timestamp":1598229715000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8460730\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5]]},"references-count":34,"URL":"https:\/\/doi.org\/10.1109\/icra.2018.8460730","relation":{},"subject":[],"published":{"date-parts":[[2018,5]]}}}