Open Access
Issue
ITM Web Conf.
Volume 25, 2019
2018 3rd International Conference on Intelligent Computing and Cognitive Informatics (ICICCI 2018)
Article Number 01015
Number of page(s) 3
Section Intelligent Computing
DOI https://doi.org/10.1051/itmconf/20192501015
Published online 01 February 2019
  1. Heinzmann, J., & Zelinsky, A. (2003). Quantitative safety guarantees for physical human-robot interaction. The International Journal of Robotics Research, 22(7-8), 479-504. [CrossRef] [Google Scholar]
  2. Tamura, Y., Le, P. D., Hitomi, K., & Chandrasiri, N. P. (2012). Development of pedestrian behavior model taking account of intention. IEEE/RSJ International Conference on Intelligent Robots & Systems. [Google Scholar]
  3. Kulić, D., & Croft, E. (2007). Pre-collision safety strategies for human-robot interaction. Autonomous Robots, 22(2), 149-164. [CrossRef] [Google Scholar]
  4. Calinon, S., D'halluin, F., Sauser, E. L., Caldwell, D. G., & Billard, A. G. (2010). Learning and reproduction of gestures by imitation. IEEE Robotics & Automation Magazine, 17(2), 44-54. [CrossRef] [Google Scholar]
  5. Ricardez, G. A. G., Yamaguchi, A., Takamatsu, J., & Ogasawara, T. (2013, November). Withdrawal strategy for human safety based on a virtual force model. In Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on (pp. 1119-1124). IEEE. [CrossRef] [Google Scholar]
  6. Ceriani, N. M., Zanchettin, A. M., Rocco, P., Stolt, A., & Robertsson, A. (2013, November). A constraint-based strategy for task-consistent safe human-robot interaction. In Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on (pp. 4630-4635). IEEE. [CrossRef] [Google Scholar]
  7. Charalampous, K., Kostavelis, I., & Gasteratos, A. (2016). Robot navigation in large-scale social maps: An action recognition approach. Expert Systems with Applications, 66, 261-273. [CrossRef] [Google Scholar]
  8. Złotowski, J., Yogeeswaran, K., & Bartneck, C. (2017). Can we control it? Autonomous robots threaten human identity, uniqueness, safety, and resources. International Journal of Human-Computer Studies, 100, 48-54. [CrossRef] [Google Scholar]
  9. Weidner, R., Kong, N., & Wulfsberg, J. P. (2013). Human Hybrid Robot: a new concept for supporting manual assembly tasks. Production Engineering, 7(6), 675-684. [CrossRef] [Google Scholar]
  10. Michalos, G., Makris, S., Tsarouchi, P., Guasch, T., Kontovrakis, D., & Chryssolouris, G. (2015). Design considerations for safe human-robot collaborative workplaces. Procedia CIrP, 37, 248-253. [CrossRef] [Google Scholar]
  11. Faber, M., Bützler, J., & Schlick, C. M. (2015). Human-robot cooperation in future production systems: analysis of requirements for designing an ergonomic work system. Procedia Manufacturing, 3, 510-517. [CrossRef] [Google Scholar]
  12. Guerrero, C. R., Marinero, J. C. F., Turiel, J. P., & Muñoz, V. (2013). Using “human state aware” robots to enhance physical human–robot interaction in a cooperative scenario. Computer methods and programs in biomedicine, 112(2), 250-259. [CrossRef] [Google Scholar]
  13. Guiochet, J. (2016). Hazard analysis of human–robot interactions with HAZOP–UML. Safety science, 84, 225-237. [CrossRef] [Google Scholar]
  14. Macfarlane, S., & Croft, E. A. (2003). Jerk-bounded manipulator trajectory planning: design for real-time applications. IEEE Transactions on Robotics and Automation, 19(1), 42-52. [CrossRef] [Google Scholar]
  15. ISO 10218:1992. Manipulating industrial robots Safety manual. [Google Scholar]
  16. Gaskill, S. P., & Went, S. R. G. (1996). Safety issues in modern applications of robots. Reliability Engineering & System Safety, 53(3), 301-307. [CrossRef] [Google Scholar]
  17. Calinon, S., D'halluin, F., Sauser, E. L., Caldwell, D. G., & Billard, A. G. (2010). Learning and reproduction of gestures by imitation. IEEE Robotics & Automation Magazine, 17(2), 44-54. [CrossRef] [Google Scholar]
  18. Gaskill, S. P., & Went, S. R. G. (1996). Safety issues in modern applications of robots. Reliability Engineering & System Safety, 53(3), 301-307. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.