Investigation of human-like haptic interaction between flying and ground robots

Date

2024-4

Author

Ak, Hatem

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Human-robot collaboration and robot-robot collaboration are common in many industries. Human-human haptic interaction is the focus of this field's innovative research and studies. Essentially, human sensorimotor functions have been modelled and applied in human-robot and robot-robot research. This thesis investigates research on human-human haptic interaction in the context of flying and ground robot interactions. A flying-ground robot system has been created that is connected by a tether. This system is an example of the leader-follower paradigm. With the sensors in the system, the follower knows its position, velocity, acceleration and the force produced on the tether. The reason for this is to use a minimum number of sensors in the system. In the human-human haptic interaction studies in the literature, the position and velocity of the partner with the force on the tether and the target position and velocity followed by the partner can be estimated. With the application of these studies to this system, the position and velocity of the leader and the target which is followed by the leader can be estimated using the force on the tether. According to the research, estimating the leader's position and velocity results in a more harmonious movement. In this thesis, the aim is to improve the target tracking performance of the follower by estimating the target position and velocity. The conducted studies in the literature have been discussed in the manner of techniques of estimating the position and velocity of the leader and target in similar cases which is a leader-follower paradigm. As a different method, the Kalman Filter is designed based on the motion models. Less sensitive and more accurate results are obtained with the Kalman Filter. By using the estimated leader position and velocity, the target position and velocity are estimated. For this purpose, the internal model of the leader is created and the Kalman Filter is designed. With the estimation of target position and velocity, the follower can track the target better, although it does not have any information about the target.

Subject Keywords

Haptic interaction, Kalman filter, State estimation, Motion models

URI

https://hdl.handle.net/11511/109807

Collections

Graduate School of Natural and Applied Sciences, Thesis