{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T21:15:54Z","timestamp":1726089354495},"publisher-location":"Cham","reference-count":41,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030503338"},{"type":"electronic","value":"9783030503345"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-50334-5_24","type":"book-chapter","created":{"date-parts":[[2020,7,9]],"date-time":"2020-07-09T23:21:31Z","timestamp":1594336891000},"page":"353-368","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Prediction-Based Uncertainty Estimation for Adaptive Crowd Navigation"],"prefix":"10.1007","author":[{"given":"Kapil D.","family":"Katyal","sequence":"first","affiliation":[]},{"given":"Katie","family":"Popek","sequence":"additional","affiliation":[]},{"given":"Gregory D.","family":"Hager","sequence":"additional","affiliation":[]},{"given":"I-Jeng","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Chien-Ming","family":"Huang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,7,10]]},"reference":[{"key":"24_CR1","doi-asserted-by":"crossref","unstructured":"Katyal, K., Hager, G.D., Huang, C.-M.: Intent-aware pedestrian prediction for adaptive crowd navigation. In: 2020 International Conference on Robotics and Automation (ICRA) (2020)","DOI":"10.1109\/ICRA40945.2020.9197434"},{"key":"24_CR2","doi-asserted-by":"crossref","unstructured":"Katyal, K., Popek, K., Paxton, C., Burlina, P., Hager, G.D.: Uncertainty-aware occupancy map prediction using generative networks for robot navigation. In: 2019 International Conference on Robotics and Automation (ICRA), pp. 5453\u20135459, May 2019","DOI":"10.1109\/ICRA.2019.8793500"},{"key":"24_CR3","doi-asserted-by":"crossref","unstructured":"Finn, C., Levine, S.: Deep visual foresight for planning robot motion. In: 2017 IEEE International Conference on Robotics and Automation (ICRA), pp. 2786\u20132793. IEEE (2017)","DOI":"10.1109\/ICRA.2017.7989324"},{"key":"24_CR4","doi-asserted-by":"crossref","unstructured":"Levine, S., Pastor, P., Krizhevsky, A., Quillen, D.: Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection. arXiv preprint arXiv:1603.02199 (2016)","DOI":"10.1007\/978-3-319-50115-4_16"},{"key":"24_CR5","unstructured":"Oh, J., Guo, X., Lee, H., Lewis, R.L., Singh, S.: Action-conditional video prediction using deep networks in Atari games. In: Cortes, C., Lawrence, N.D., Lee, D.D., Sugiyama, M., Garnett, R., Garnett, R. (eds.) Advances in Neural Information Processing Systems 28, pp. 2845\u20132853. Curran Associates Inc. (2015)"},{"key":"24_CR6","unstructured":"Ulyanov, D., Vedaldi, A., Lempitsky, V.S.: Deep image prior. CoRR, vol. abs\/1711.10925 (2017). http:\/\/arxiv.org\/abs\/1711.10925"},{"key":"24_CR7","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. In: Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N.D., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems 27, pp. 2672\u20132680. Curran Associates Inc. (2014). http:\/\/papers.nips.cc\/paper\/5423-generative-adversarial-nets.pdf"},{"key":"24_CR8","doi-asserted-by":"crossref","unstructured":"Isola, P., Zhu, J.-Y., Zhou, T., Efros, A.A.: Image-to-image translation with conditional adversarial networks. In: CVPR (2017)","DOI":"10.1109\/CVPR.2017.632"},{"key":"24_CR9","doi-asserted-by":"crossref","unstructured":"Tamar, A., Wu, Y., Thomas, G., Levine, S., Abbeel, P.: Value iteration networks. In: Advances in Neural Information Processing Systems, pp. 2154\u20132162 (2016)","DOI":"10.24963\/ijcai.2017\/700"},{"key":"24_CR10","doi-asserted-by":"crossref","unstructured":"Tai, L., Paolo, G., Liu, M.: Virtual-to-real deep reinforcement learning: continuous control of mobile robots for mapless navigation. CoRR, vol. abs\/1703.00420 (2017). http:\/\/arxiv.org\/abs\/1703.00420","DOI":"10.1109\/IROS.2017.8202134"},{"key":"24_CR11","doi-asserted-by":"crossref","unstructured":"Kahn, G., Villaflor, A., Ding, B., Abbeel, P., Levine, S.: Self-supervised deep reinforcement learning with generalized computation graphs for robot navigation. CoRR, vol. abs\/1709.10489 (2017). http:\/\/arxiv.org\/abs\/1709.10489","DOI":"10.1109\/ICRA.2018.8460655"},{"issue":"12","key":"24_CR12","doi-asserted-by":"publisher","first-page":"1726","DOI":"10.1016\/j.robot.2013.05.007","volume":"61","author":"T Kruse","year":"2013","unstructured":"Kruse, T., Pandey, A.K., Alami, R., Kirsch, A.: Human-aware robot navigation: a survey. Robot. Auton. Syst. 61(12), 1726\u20131743 (2013)","journal-title":"Robot. Auton. Syst."},{"key":"24_CR13","doi-asserted-by":"crossref","unstructured":"van den Berg, J.P., Lin, M.C., Manocha, D.: Reciprocal velocity obstacles for real-time multi-agent navigation. In: 2008 IEEE International Conference on Robotics and Automation, pp. 1928\u20131935 (2008)","DOI":"10.1109\/ROBOT.2008.4543489"},{"key":"24_CR14","series-title":"Springer Tracts in Advanced Robotics","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-642-19457-3_1","volume-title":"Robotics Research","author":"J van den Berg","year":"2011","unstructured":"van den Berg, J., Guy, S.J., Lin, M., Manocha, D.: Reciprocal n-body collision avoidance. In: Pradalier, C., Siegwart, R., Hirzinger, G. (eds.) Robotics Research. STAR, vol. 70, pp. 3\u201319. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-19457-3_1"},{"key":"24_CR15","doi-asserted-by":"crossref","unstructured":"Phillips, M., Likhachev, M.: SIPP: safe interval path planning for dynamic environments, pp. 5628\u20135635, June 2011","DOI":"10.1109\/ICRA.2011.5980306"},{"issue":"1","key":"24_CR16","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1007\/s10514-013-9334-3","volume":"35","author":"GS Aoude","year":"2013","unstructured":"Aoude, G.S., Luders, B.D., Joseph, J.M., Roy, N., How, J.P.: Probabilistically safe motion planning to avoid dynamic obstacles with uncertain motion patterns. Auton. Robots 35(1), 51\u201376 (2013). https:\/\/doi.org\/10.1007\/s10514-013-9334-3","journal-title":"Auton. Robots"},{"issue":"11","key":"24_CR17","doi-asserted-by":"publisher","first-page":"1289","DOI":"10.1177\/0278364915619772","volume":"35","author":"H Kretzschmar","year":"2016","unstructured":"Kretzschmar, H., Spies, M., Sprunk, C., Burgard, W.: Socially compliant mobile robot navigation via inverse reinforcement learning. Int. J. Robot. Res. 35(11), 1289\u20131307 (2016). https:\/\/doi.org\/10.1177\/0278364915619772","journal-title":"Int. J. Robot. Res."},{"key":"24_CR18","doi-asserted-by":"crossref","unstructured":"Everett, M., Chen, Y.F., How, J.P.: Motion planning among dynamic, decision-making agents with deep reinforcement learning. In: IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, September 2018. https:\/\/arxiv.org\/pdf\/1805.01956.pdf","DOI":"10.1109\/IROS.2018.8593871"},{"key":"24_CR19","doi-asserted-by":"crossref","unstructured":"Chen, C., Liu, Y., Kreiss, S., Alahi, A.: Crowd-robot interaction: crowd-aware robot navigation with attention-based deep reinforcement learning (2018)","DOI":"10.1109\/ICRA.2019.8794134"},{"key":"24_CR20","unstructured":"Kahn, G., Villaflor, A., Pong, V., Abbeel, P., Levine, S.: Uncertainty-aware reinforcement learning for collision avoidance. arXiv, vol. abs\/1702.01182 (2017)"},{"key":"24_CR21","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. CoRR, vol. abs\/1505.04597 (2015). http:\/\/arxiv.org\/abs\/1505.04597"},{"key":"24_CR22","unstructured":"Johnson, J., Alahi, A., Li, F.: Perceptual losses for real-time style transfer and super-resolution. CoRR, vol. abs\/1603.08155 (2016). http:\/\/arxiv.org\/abs\/1603.08155"},{"key":"24_CR23","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. CoRR, vol. abs\/1512.03385 (2015). http:\/\/arxiv.org\/abs\/1512.03385"},{"key":"24_CR24","doi-asserted-by":"crossref","unstructured":"Zhu, J., Park, T., Isola, P., Efros, A.A.: Unpaired image-to-image translation using cycle-consistent adversarial networks. CoRR, vol. abs\/1703.10593 (2017). http:\/\/arxiv.org\/abs\/1703.10593","DOI":"10.1109\/ICCV.2017.244"},{"key":"24_CR25","doi-asserted-by":"crossref","unstructured":"Hornung, A., Wurm, K.M., Bennewitz, M., Stachniss, C., Burgard, W.: OctoMap: an efficient probabilistic 3D mapping framework based on octrees. Auton. Robots (2013). http:\/\/octomap.github.com","DOI":"10.1007\/s10514-012-9321-0"},{"key":"24_CR26","unstructured":"Min, P.: Binvox (2004\u20132017). http:\/\/www.patrickmin.com\/binvox. Accessed 20 Feb 2017"},{"issue":"2","key":"24_CR27","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1109\/TVCG.2003.1196006","volume":"9","author":"FS Nooruddin","year":"2003","unstructured":"Nooruddin, F.S., Turk, G.: Simplification and repair of polygonal models using volumetric techniques. IEEE Trans. Vis. Comput. Graph. 9(2), 191\u2013205 (2003)","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"24_CR28","unstructured":"Paszke, A., et al.: Automatic Differentiation in PyTorch (2017)"},{"key":"24_CR29","doi-asserted-by":"crossref","unstructured":"Rupprecht, C., Laina, I., Baust, M., Tombari, F., Hager, G.D., Navab, N.: Learning in an uncertain world: representing ambiguity through multiple hypotheses. CoRR, vol. abs\/1612.00197 (2016). http:\/\/arxiv.org\/abs\/1612.00197","DOI":"10.1109\/ICCV.2017.388"},{"key":"24_CR30","doi-asserted-by":"crossref","unstructured":"Hess, W., Kohler, D., Rapp, H., Andor, D.: Real-time loop closure in 2D LIDAR SLAM. In: IEEE International Conference on Robotics and Automation (ICRA) 2016, pp. 1271\u20131278 (2016)","DOI":"10.1109\/ICRA.2016.7487258"},{"key":"24_CR31","unstructured":"Yamauchi, B.: A frontier-based approach for autonomous exploration. In: Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 1997. \u2018Towards New Computational Principles for Robotics and Automation\u2019, pp. 146\u2013151, July 1997"},{"key":"24_CR32","doi-asserted-by":"crossref","unstructured":"Bai, S., Wang, J., Chen, F., Englot, B.: Information-theoretic exploration with Bayesian optimization. In: 2016 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1816\u20131822. IEEE (2016)","DOI":"10.1109\/IROS.2016.7759289"},{"key":"24_CR33","unstructured":"Bai, S., Wang, J., Doherty, K., Englot, B.: Inference-enabled information-theoretic exploration of continuous action spaces. In: International Symposium of Robotics Research (2015)"},{"key":"24_CR34","doi-asserted-by":"crossref","unstructured":"Wirth, S., Pellenz, J.: Exploration transform: a stable exploring algorithm for robots in rescue environments. In: IEEE International Workshop on Safety, Security and Rescue Robotics: SSRR 2007, pp. 1\u20135. IEEE (2007)","DOI":"10.1109\/SSRR.2007.4381274"},{"key":"24_CR35","unstructured":"Brockman, G., et al.: OpenAI Gym. CoRR, vol. abs\/1606.01540 (2016). http:\/\/arxiv.org\/abs\/1606.01540"},{"key":"24_CR36","doi-asserted-by":"crossref","unstructured":"Chen, Y.F., Liu, M., Everett, M., How, J.: Decentralized non-communicating multiagent collision avoidance with deep reinforcement learning, pp. 285\u2013292, May 2017","DOI":"10.1109\/ICRA.2017.7989037"},{"key":"24_CR37","unstructured":"Fan, R.-E., Chang, K.-W., Hsieh, C.-J., Wang, X.-R., Lin, C.-J.: LIBLINEAR: a library for large linear classification. J. Mach. Learn. Res. 9, 1871\u20131874 (2008). http:\/\/dl.acm.org\/citation.cfm?id=1390681.1442794"},{"key":"24_CR38","doi-asserted-by":"crossref","unstructured":"Gupta, A., Johnson, J., Fei-Fei, L., Savarese, S., Alahi, A.: Social GAN: socially acceptable trajectories with generative adversarial networks. CoRR, vol. abs\/1803.10892 (2018). http:\/\/arxiv.org\/abs\/1803.10892","DOI":"10.1109\/CVPR.2018.00240"},{"key":"24_CR39","doi-asserted-by":"crossref","unstructured":"Efron, B.: The Jackknife, The Bootstrap and Other Resampling Plans. ser. CBMS-NSF Regional Conference Series in Applied Mathematics. SIAM, Philadelphia (1982). Lectures Given at Bowling Green State Univ., June 1980. https:\/\/cds.cern.ch\/record\/98913","DOI":"10.1137\/1.9781611970319"},{"key":"24_CR40","unstructured":"Gal, Y., Ghahramani, Z.: Dropout as a Bayesian approximation: representing model uncertainty in deep learning. In: Balcan, M.F., Weinberger, K.Q. (eds.) Proceedings of the 33rd International Conference on Machine Learning, ser. Proceedings of Machine Learning Research, PMLR, New York, NY, USA, 20\u201322 June 2016, vol. 48, pp. 1050\u20131059 (2016). http:\/\/proceedings.mlr.press\/v48\/gal16.html"},{"key":"24_CR41","unstructured":"Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1), 1929\u20131958 (2014). http:\/\/dl.acm.org\/citation.cfm?id=2627435.2670313"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence in HCI"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-50334-5_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T00:45:52Z","timestamp":1720572352000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-50334-5_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030503338","9783030503345"],"references-count":41,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-50334-5_24","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"10 July 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HCII","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Human-Computer Interaction","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Copenhagen","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Denmark","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19 July 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 July 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"hcii2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2020.hci.international\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}