- PhD in Robotics, Paris 6 (UPMC), Paris, France
- Engineer in Radioelectronics, Tomsk State Univeristy of Control Systems and Radioelectronics (TUSUR), Russia (Siberia)
- Toyota student participation, ISER 2016, Tokyo, Japan
- 2016 SIGMA, Institute Pascal, France
- 2015 Key State Institute of Robotics, Shengyang, China “European and Chinese Platform for Robotics and Applications (ECROBOT)
- Sense of touch
Multifingered robotic hands and dexterous manipulation
Tactile Sensing for autonomous systems
- Mechatronics: 3D rapid Prototyping and Design
- Power electronics – phtotovoltaic inverters
- Teaching Assistant of the Robotics Department at Nazarbayev University. Development of 3D printed robotic hand. 2011-2013.
- Engineer at Research Institute of Automatics and Electromechanics, Tomsk (Siberia), Russia. 2010 – 2011.
- Intern. Industrial Technology Research Institute (ITRI), Taiwan. 2010.
Autonomous manipulation comprises several disciplines like computer vision, force control, human-robot interaction and etc, which is not far not full lest of theories. The integration of control and computational techniques is yet in challenge. Robot Operating System (ROS) is very popular in Robotics community. We use ROS to control Dexterous Robot Hand.
Autonomous manipulation requires continuous tactile feedback, there are some approaches that use visual information though. Using only vision for manipulation is sealed to fail. Possible occlusions in unstructured environment, absence of information about contact geometry, safe human-robot interaction and etc. Also, actuation of robot hands is far from ideal. Some-time when grasp (we use coded into control laws synergies to grasp) is performed, fingers may move and loose the contact with an object due to noise in encoders in the joints, current sensing readings ( in Shadow hand force gouges are used for tendons’ tension readings). To keep the fingers in the contact reactive finger motion is needed.
Tactile sensor tightly bounded with motors in control algorithms is a key thing for solution above problem. There are approaches of slip detection, but most of them implemented in simple grippers and three-fingered robot hands. Implementing slip detection algorithms in dexterous hands like Shadow is a challenging task since they have a lot of DoFs.
Another challenging task is in-hand manipulation based on Tactile Sensors. Tactile sensing arrays provide robot hand with “grey-scale” image. Location and pressure of contact points are very important information for manipulation. There are tactile servoing techniques, first of tactile servoing algorithm was introduced by Zhang et al. in 2000. However, there are no control algorithms for tactile servoing algorithms for several tactile arrays, that are placed on the fingers and the palm. Current approaches use only one flat array and 6 DoF manipulators.
My research work is focused on investigation and development new control algorithms for dexterous autonomous manipulation with robot hands equipped with tactile sensing modalities. More precisely: multi-array tactile servoing and reactive grasp based on tactile information.
В самом деле, только звук и мышечное ощущение дают человеку представление о времени, притом не всем своим содержанием, а лишь одною стороною, тягучестью звука и тягучестью мышечного чувства. Перед моими глазами двигается предмет; следя за ним, я двигаю постепенно или головой, или глазами, или обоими вместе; во всяком случае зрительное ощущение ассоциируется с тянущимся ощущением сокращающихся мышц.
Vásquez, A., Kappassov, Z., Perdereau, V., 2016 IEEE International Conference on Intelligent Robots and Systems. Institute of Electrical and Electronics Engineers Inc., p. 965-970
Tactile sensing in dexterous robot hands - Review
Kappassov, Z., Corrales, J., Perdereau, V., 2015 Robotics and Autonomous Systems. Elsevier, p. 195-220
Semi-anthropomorphic 3D printed multigrasp hand for industrial and service robots
Kappassov, Z., Khassanov, Y., Saudabayev, A., Shintemirov, A., Varol, H., 2013 2013 IEEE International Conference on Mechatronics and Automation, IEEE ICMA 2013. p. 1697-1702