Koh Hosoda Pengarang

An estimation method of end-point impedance based on bilateral control system Toshiaki Okanoa, Kouhei Ohnishib and Toshiyuki Murakamic aGraduate School of Science and Technology, Keio University, Yokohama, Japan; bHaptics Research Center 7-1, Kawasaki, Japan; cDepartment of System Design Engineering, Keio University, Yokohama, Japan ABSTR AC T This paper aims at developing an estimation method of end-point impedance. Human operators are constantly changing their end-point impedance for adapting to the surrounded environment and executing some complicated tasks, and it is highly meaningful to investigate these variations for the further understanding of human motion. Most of the conventional researches, however, have considered non-contact-point impedance or tasks that is only holding the vibrated sticks due to the experimental constraints. This paper proposes the estimation method of end-point impedance by using bilateral control system. The extra signal is added to the force controller for the impedance estimation. In addition, the effect of the bilateral controller is estimated and removed from the impedance estimation process for securing the applicability of moving tasks. The proposed method was validated through simulations and an experiment. The experimental result showed that the endpoint stiffness can be estimated properly even if the operator robot was moving and changed its end-point impedance. KEY WORDS Haptics; motion control; bilateral control system; impedance estimation Computational model for tactile sensing system with wrinkle’s morphological change Hiep Xuan Trinha, Van Anh Hob and Koji Shibuyaa aDepartment of Mechanical and System Engineering, Ryukoku University, Otsu, Shiga, Japan; bSchool of Materials Science, Japan Advanced Institute of Science and Technology (JAIST), Nomi, Ishikawa, Japan ABSTR AC T We previously developed Wrin’Tac, a tactile sensing system that can select sensing modalities by changing its morphology. In this paper, we present a computational model to estimate a wrinkle’s morphology and predict the output of embedded sensing elements in both static indentation and sliding action cases. We evaluated the wrinkle shape and the posture of the sensing element by calculating its height. The wrinkle’s mechanical change is assessed by ascertaining its stiffness under vertical indentation by a spherical indenter. The output voltages of the sensor under static indentation are calculated by the proposed model, and the experimental values have error less than 10%, which validates the accuracy of our proposed model. For dynamic sliding action, this proposed model clarified the capability of wrinkle morphology in an evaluation of such sliding action’s characteristics as the sliding direction and velocity. We also identified the role of the wrinkle’s morphology in the sensor’s sensitivity under different conditions of dynamic sliding motion, implying that this sensing system may select suitable sensitivity for specific sensation tasks. We expect this work to pave the way for assessing the role of morphological changes to tactile sensation and developing soft active tactile sensing systems. KEY WORDS Morphological computation; tactile sensing system; contact modeling Localized online learning-based control of a soft redundant manipulator under variable loading J u s t i n D . L . H oa, Kit-Hang Leea, Wai Lun Tanga, Ka-Ming Huia, Kaspar Althoeferb, James Lama and Ka-Wai Kwoka aDepartment of Mechanical Engineering, The University of Hong Kong, Hong Kong, China; bCentre for Advanced Robotics @ Queen Mary, School of Engineering and Materials Science, Queen Mary University of London, London, UK ABSTR AC T Soft robots are inherently compliant and manoeuvrable manipulators that can passively adapt to their environment. However, in order to fully make use of their unique properties, accurate control should still be maintained when affected by external loading. Commonly used model-based approaches often have low tolerance to unmodelled loading, resulting in significant error when acted on by them. Therefore, in this study we employ a nonparametric learning-based method that can approximate and update the inverse model of a redundant two-segment soft robot in an online manner. The primary contribution of this work is the application and evaluation of the proposed framework on a redundant soft robot. With the addition of redundancy, a constrained optimization approach is taken to consistently resolve null-space behaviour. Through this control framework, the controller can continuously adapt to unknown external disturbances during runtime and maintain end-effector accuracy. The performance of the control framework was evaluated by tracking of a 3D trajectory with a static tip load, and a variable weight tip load. The results indicate that the proposed controller could effectively adapt to the disturbances and continue to track the desired trajectory accurately. KEY WORDS Soft robotics; modelling; compliance; machine learning Wearable artificial skin layer for the reconstruction of touched geometry by morphological computation Toshinobu Takeia, Mitsuhito Andob and Hiromi Mochiyamab aDepartment of Mechanical Science and Engineering, Hirosaki University, Aomori, Japan; bDepartment of Intelligent Interaction Technologies, University of Tsukuba, Ibaraki, Japan ABSTR AC T This paper proposes a wearable haptic sensor for the reconstruction of the surface geometry of an object to be touched. The proposed haptic sensor is a thin rubber artificial skin layer that is formed around the user’s finger or other body part and contains a small embedded strain gauge for measuring large deformations. The sensor can be easily fabricated by rubber dipping. First, it was demonstrated that the proposed sensor is not only able to statically detect the curvature of the touched surface but can also measure deformations due to rapid light tapping with robustness against motion noise. As an illustrative demonstration of morphological computation in haptics, it was then demonstrated that it is possible to reconstruct the geometry of tiny undulations in the surface of the touched object from the information obtained by the proposed sensor. KEY WORDS Soft robotics; morphological computation; haptics; tactile sensor