| Modeling of deformable objects for robotic manipulation: A tutorial and review VE Arriola-Rios, P Guler, F Ficuciello, D Kragic, B Siciliano, JL Wyatt Frontiers in Robotics and AI 7, 82, 2020 | 99 | 2020 |
| A multimodal model of object deformation under robotic pushing VE Arriola-Rios, JL Wyatt IEEE Transactions on Cognitive and Developmental Systems 9 (2), 153-169, 2017 | 32 | 2017 |
| How to build an information gathering and processing system: Lessons from naturally and artificially intelligent systems J Chappell, ZP Demery, V Arriola-Rios, A Sloman Behavioural Processes 89 (2), 179-186, 2012 | 14 | 2012 |
| 2D Mass-spring-like Model for Prediction of a Sponge’s Behaviour upon Robotic Interaction VE Arriola-Rios, J Wyatt International Conference on Innovative Techniques and Applications of …, 2011 | 4 | 2011 |
| Construct to Understand: Learning through Exploration Z Demery, VEA Rios, A Sloman, J Wyatt, J Chappell | 3* | |
| Learning to predict the behaviour of deformable objects through and for robotic interaction VE Arriola Rios University of Birmingham, 2013 | 2 | 2013 |
| Salient Features and Snapshots in Time: an interdisciplinary perspective on object representation VE Arriola-Rios, ZP Demery, J Wyatt, A Sloman, J Chappell Computing Nature: Turing Centenary Perspective, 171-184, 2013 | 2 | 2013 |
| Knowledge acquisition and automatic generation of rules for the inference machine CLIPS V Arriola, J Savage MICAI 2007: Advances in Artificial Intelligence, 725-735, 2007 | 1 | 2007 |
Jeremy L WyattDirector, Applied Science, Amazonamazon.com의 이메일 확인됨
