Situation assessment through multi-modal sensing of dynamic environments to support cognitive robot control

1. M. Endsley, 2000, Theoretical underpinnings of Situation Awareness: a critical review, Situation Awareness Analysis and Measurement, Mahwah, NJ. 2. Blasch, E & S. Plano, 2002, JDL Level 5 fusion model: user refinement issues and applications in group tracking, SPIE Vol. 4729, Aerosense, pp. 270 – 279. 3. Wahde, M., 2009, A general-purpose method for decision-making in autonomous robots. IEA/AIE, Vol. 5579 of Lecture Notes in Computer Science. 4. Ye, J., Dobson, S., McKeever, S., 2011, Situation identification techniques in pervasive computing, Pervasive & Mobile computing. 5. Boytsov, A. & Zaslavsky, A., 2011, From Sensory Data to Situation Awareness – Enhanced Context Spaces Theory Approach. 9th IEEE Int. Conf. Dependable, Autonomic and Secure Computing. 6. Zhang, M. & Sawchuk, A.A., 2011, A Feature Selection-Based Frame-work for Human Activity Recognition Using Wearable Multimodal Sensors, Proc. Int. Conf. Body Area Networks, Beijing. 7. Vaughan, C.L., Davis, B.L., O’Connor, J.C., 1992, Dynamics of Human Gait , 2nd ed., Kiboho Publishers South Africa. 8. Shafer, G., 1976, A Mathematical Theory of Evidence, Princeton University Press. 9. Dempster, A. P., 1967, Upper and lower probabilities induced by a multivalued mapping, The Annals of Mathematical Statistics 38 (2), pp. 325–339. 10. CORBYS project, 2014. CORBYS. [online] Available at: http://www.corbys.eu (accessed 10. Nov. 2014).