Haptic Object Identification for Advanced Manipulation Skills
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Automation, pp. 342–347. IEEE Computer Society Press (1989)
2. Behbahani, F.: Reverse-Engineering The Visual and Haptic Perceptual Algorithms
in The Brain. Doctor of philosophy, Imperial College London (2016)
3. Behbahani, F., Taunton, R., Thomik, A., Faisal, A.: Haptic SLAM for contextaware robotic hand prosthetics - simultaneous inference of hand pose and object
shape using particle filters. In: International IEEE/EMBS Conference on Neural
Engineering, NER, vol. 1229297, 719–722 (2015)
4. Bourgault, F., Makarenko, A., Williams, S., Grocholsky, B., Durrant-Whyte, H.:
Information based adaptive robotic exploration. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, October 2002, pp. 540–545 (2002)
5. Decherchi, S., Gastaldo, P., Dahiya, R., Valle, M., Zunino, R.: Tactile-data classification of contact materials using computational intelligence. IEEE Trans. Rob.
3, 635–639 (2011)
6. Durrant-Whyte, H., Bailey, T.: Simultaneous localization and mapping: Part I.
IEEE Robot. Autom. Mag. 13(2), 99–108 (2006)
7. Elfes, A.: Using occupancy grids for mobile robot perception and navigation. Computer 22(6), 46–57 (1989)
8. Elfes, A.: Robot navigation: integrating perception, environmental constraints and
task execution within a probabilistic framework. In: Dorst, L., van Lambalgen, M.,
Voorbraak, F. (eds.) RUR 1995. LNCS, vol. 1093, pp. 91–130. Springer, Heidelberg
(1996). https://doi.org/10.1007/BFb0013955
9. Fishel, J., Loeb, G.: Bayesian exploration for intelligent identification of textures.
Front. Neurorobot. 1–20, (2012)
10. Friedl, K.E., Voelker, A.R., Peer, A., Eliasmith, C.: Human-inspired neurorobotic
system for classifying surface textures by touch. IEEE Robot. Autom. Lett. 1,
516–523 (2016)
11. Hegazy, D., Denzler, J.: Combining appearance and range based information for
multi-class generic object recognition. In: Bayro-Corrochano, E., Eklundh, J.-O.
(eds.) CIARP 2009. LNCS, vol. 5856, pp. 741–748. Springer, Heidelberg (2009).
https://doi.org/10.1007/978-3-642-10268-4 87
12. Julian, B., Angermann, M., Schwager, M., Rus, D.: Distributed robotic sensor
networks: an information-theoretic approach. Int. J. Robot. Res. 10, 1134–1154
(2012)
13. Luo, S., Bimbo, J., Dahiya, R., Liu, H.: Robotic tactile perception of object properties: a review. Mechatronics 18, 54–67 (2017)
14. Martinez-Hernandez, U., Metta, G., Dodd, T., Prescott, T., Natale, L., Lepora,
N.: Active contour following to explore object shape with robot touch. In: 2013
World Haptics Conference, WHC 2013, pp. 341–346 (2013)
15. Montemerlo, M., Thrun, S., Koller, D., Webreit, B.: FastSLAM: a factored solution
to the simultaneous localization and mapping problem. In: AAAI/IAAI, pp. 593–
598 (2002)
16. Navarro, S., Gorges, N., W¨ orn, H., Schill, J., Asfour, T., Dillmann, R.: Haptic
object recognition for multi-fingered robot hands. In: 2012 IEEE Haptics Symposium, HAPTICS 2012, pp. 497–502. IEEE (2012)
17. Pezzementi, Z., Plaku, E., Reyda, C., Hager, G.: Tactile-object recognition from
appearance information. IEEE Trans. Rob. 3, 473–487 (2011)
139
References
1. Allen, P., Roberts, K.: Haptic object recognition using a multi-fingered dextrous
hand. In: Proceedings of the 1989 IEEE International Conference on Robotics and
Automation, pp. 342–347. IEEE Computer Society Press (1989)
2. Behbahani, F.: Reverse-Engineering The Visual and Haptic Perceptual Algorithms
in The Brain. Doctor of philosophy, Imperial College London (2016)
3. Behbahani, F., Taunton, R., Thomik, A., Faisal, A.: Haptic SLAM for contextaware robotic hand prosthetics - simultaneous inference of hand pose and object
shape using particle filters. In: International IEEE/EMBS Conference on Neural
Engineering, NER, vol. 1229297, 719–722 (2015)
4. Bourgault, F., Makarenko, A., Williams, S., Grocholsky, B., Durrant-Whyte, H.:
Information based adaptive robotic exploration. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, October 2002, pp. 540–545 (2002)
5. Decherchi, S., Gastaldo, P., Dahiya, R., Valle, M., Zunino, R.: Tactile-data classification of contact materials using computational intelligence. IEEE Trans. Rob.
3, 635–639 (2011)
6. Durrant-Whyte, H., Bailey, T.: Simultaneous localization and mapping: Part I.
IEEE Robot. Autom. Mag. 13(2), 99–108 (2006)
7. Elfes, A.: Using occupancy grids for mobile robot perception and navigation. Computer 22(6), 46–57 (1989)
8. Elfes, A.: Robot navigation: integrating perception, environmental constraints and
task execution within a probabilistic framework. In: Dorst, L., van Lambalgen, M.,
Voorbraak, F. (eds.) RUR 1995. LNCS, vol. 1093, pp. 91–130. Springer, Heidelberg
(1996). https://doi.org/10.1007/BFb0013955
9. Fishel, J., Loeb, G.: Bayesian exploration for intelligent identification of textures.
Front. Neurorobot. 1–20, (2012)
10. Friedl, K.E., Voelker, A.R., Peer, A., Eliasmith, C.: Human-inspired neurorobotic
system for classifying surface textures by touch. IEEE Robot. Autom. Lett. 1,
516–523 (2016)
11. Hegazy, D., Denzler, J.: Combining appearance and range based information for
multi-class generic object recognition. In: Bayro-Corrochano, E., Eklundh, J.-O.
(eds.) CIARP 2009. LNCS, vol. 5856, pp. 741–748. Springer, Heidelberg (2009).
https://doi.org/10.1007/978-3-642-10268-4 87
12. Julian, B., Angermann, M., Schwager, M., Rus, D.: Distributed robotic sensor
networks: an information-theoretic approach. Int. J. Robot. Res. 10, 1134–1154
(2012)
13. Luo, S., Bimbo, J., Dahiya, R., Liu, H.: Robotic tactile perception of object properties: a review. Mechatronics 18, 54–67 (2017)
14. Martinez-Hernandez, U., Metta, G., Dodd, T., Prescott, T., Natale, L., Lepora,
N.: Active contour following to explore object shape with robot touch. In: 2013
World Haptics Conference, WHC 2013, pp. 341–346 (2013)
15. Montemerlo, M., Thrun, S., Koller, D., Webreit, B.: FastSLAM: a factored solution
to the simultaneous localization and mapping problem. In: AAAI/IAAI, pp. 593–
598 (2002)
16. Navarro, S., Gorges, N., W¨ orn, H., Schill, J., Asfour, T., Dillmann, R.: Haptic
object recognition for multi-fingered robot hands. In: 2012 IEEE Haptics Symposium, HAPTICS 2012, pp. 497–502. IEEE (2012)
17. Pezzementi, Z., Plaku, E., Reyda, C., Hager, G.: Tactile-object recognition from
appearance information. IEEE Trans. Rob. 3, 473–487 (2011)