Explorative sensor-based grasp planning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7429 LNAI, Issue , 2012, Pages 197-208

  Nikandrova, Ekaterina ^a   Laaksonen, Janne ^a   Kyrki, Ville ^a  

^a LAPPEENRANTA UNIVERSITY OF TECHNOLOGY   (Finland)

Author keywords

entropy; Grasp planning; MCMC; PSO

Indexed keywords

ENTROPY-BASED; GRASP PLANNING; MCMC; PROBABILISTIC FRAMEWORK; PROBABILISTIC MODELS; PSO; SENSORY INFORMATION;

ENTROPY;

SENSORS;

EID: 84865034969     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-32527-4_18     Document Type: Conference Paper

References (18)

1. Russell, R.A.: Object recognition by a smart tactile sensor. Image Processing, 93-98 (1984)
2. Gorges, N., Navarro, S.E., Goeger, D., Woern, A.H.: Haptic Object Recognition Using Passive Joints and Haptic Key Features. In: 2010 IEEE International Conference on Robotics and Automation (2010)
3. Hsiao, K., Kaelbling, L.P., Lozano-Pérez, T.: Task-driven tactile exploration. In: Robotics: Science and Systems (2010)
4. Corcoran, C., Platt Jr., R.: A measurement model for tracking hand-object state during dexterous manipulation. Intelligence, 4302-4308 (2010)
5. Dang, H., Weisz, J., Allen, P.K.: Blind grasping: Stable robotic grasping using tactile feedback and hand kinematics. In: ICRA, pp. 5917-5922. IEEE (2011)
6. Bekiroglu, Y., Laaksonen, J., Jorgensen, J.A., Kyrki, V., Kragic, D.: Assessing Grasp Stability Based on Learning and Haptic Data. IEEE Transactions on Robotics 27(3), 616-629 (2011)
7. Chitta, S., Piccoli, M., Sturm, J.: Tactile object class and internal state recognition for mobile manipulation. In: International Conference on Robotics and Automation, Anchorage, Alaska (2010)
8. Laaksonen, J., Kyrki, V.: Probabilistic approach to sensor-based grasping. In: ICRA 2011 Workshop: Manipulation Under Uncertainty (2011)
9. Taguchi, Y., Marks, T.K., Hershey, J.R.: Entropy-based motion selection for touch-based registration using rao-blackwellized particle filtering. In: IROS, pp. 4690-4697. IEEE (2011)
10. Suárez, R., Roa, M., Cornella, J.: Grasp quality measures. Technical report, Technical University of Catalonia (2006)
11. Hsiao, K., Ciocarlie, M., Brook, P.: Bayesian grasp planning. In: ICRA 2011 Workshop on Mobile Manipulation: Integrating Perception and Manipulation (2011)
12. Stachniss, C., Grisetti, G., Burgard, W.: Information gain-based exploration using rao-blackwellized particle filters. In: Proc. of Robotics: Science and Systems (RSS), Cambridge, MA, USA (2005)
13. Stachniss, C., Grisetti, G., Burgard, W.: Recovering particle diversity in a rao-blackwellized particle filter for slam after actively closing loops. In: ICRA, pp. 655-660 (2005)
14. Ryan, A.: Information-theoretic tracking control based on particle filter estimate. In: AIAA Guidance Navigation and Control Conference, pp. 1-15. AIAA (2008)
15. Simandl, M.: Differential entropy estimation by particles. In: 18th IFAC World Congress, pp. 11991-11996. Elsevier (2011)
16. Rasmussen, C.E., Williams, C.: Gaussian Processes for Machine Learning. MIT Press (2006)
17. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: IEEE International Conference on Neural Networks, pp. 1942-1948 (1995)
18. Miller, A.T., Miller, A.T.: Graspit!: A versatile simulator for robotic grasping. IEEE Robotics and Automation Magazine 11, 110-122 (2004)