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Robotics for graduate students,

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References

  • B. Siciliano, L. Sciavicco, L. Villani, and G. Oriolo, Robotics: Modelling, Planning and Control,
    New York, NY, USA: Springer, 2009.

  • B. Siciliano, O. Khatib, Springer Handbook of Robotics, 2008

In recent years, people have become interested in interacting with a virtual world via a virtual reality system. Haptic robots are designed to provide the sense of touch in this connection. There are various and continuously increasing applications for these robots in education, medicine, entertainment, etc.

  • Visual Servoing with Safe Interaction:  The control of the interaction during an image based/position based visual servoing for a robot working in dynamic cluttered environments is considered. The main concerns in this scenario are the performance of the main visual servoing task, keeping the visual feature in the field of view as well as a safe physical    avoidance/interaction.

 

Extracting an accurate and complete map of the world is among the most difficult tasks in mobile robotics. In this regard, enabling the mobile robot to learn the map of the world and choose the optimum destination to continue the autonomous scanning of the environment, is the topic of this research. For this purpose, the Rao-Blackwellized particle filter for occupancy grid maps is used to determine the pose of the robot and create the map of the world.

  • Constrained Kinematic Control in MIRS Subject to RCM: Novel kinematic formulations for surgical systems are derived and the movement restriction in incision point, known as RCM constraint, is resolved by active control of the system through a so-called RCM-constrained Jacobian. The proposed minimal Jacobian matrix can realize fixed/moving trocar constraint effectively in comparison with the state of the arts.

 

Physical Human Robot Interaction: The aim of this research is to study about novel control algorithms to control robot in human environment. This interaction can be either intentional or accidental.  The main idea is to estimate external interactions (without using torque sensor information) and to increase the compliance of the system relying on fast control loops. The estimated interaction is further used to derive the robot appropriately. The algorithms are mainly implemented on KUKA LWR4 and iiwa robot arm.

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