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Sampling of Pareto-Optimal Trajectories Using Progressive Objective Evaluation in Multi-Objective Motion Planning.

, , and . IROS, page 1-9. IEEE, (2018)

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Generality and Simple Hands., , and . ISRR, volume 70 of Springer Tracts in Advanced Robotics, page 345-361. Springer, (2009)Predicting User Intent Through Eye Gaze for Shared Autonomy., and . AAAI Fall Symposia, AAAI Press, (2016)Iterative Linearized Control: Stable Algorithms and Complexity Guarantees., , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 5518-5527. PMLR, (2019)Physics-based motion retiming., , and . Symposium on Computer Animation, page 205-214. Eurographics Association, (2006)Predictability or adaptivity?: designing robot handoffs modeled from trained dogs and people., , , , and . HRI, page 179-180. ACM, (2011)The Provable Virtue of Laziness in Motion Planning., , , , and . IJCAI, page 6161-6165. ijcai.org, (2019)Generalizing Informed Sampling for Asymptotically Optimal Sampling-based Kinodynamic Planning via Markov Chain Monte Carlo., , , , and . CoRR, (2017)Batch Informed Trees (BIT*): Sampling-based optimal planning via the heuristically guided search of implicit random geometric graphs., , and . ICRA, page 3067-3074. IEEE, (2015)Pareto-optimal search over configuration space beliefs for anytime motion planning., , and . IROS, page 3742-3749. IEEE, (2016)LEGO: Leveraging Experience in Roadmap Generation for Sampling-Based Planning., , , and . IROS, page 1488-1495. IEEE, (2019)