Achieving high-fidelity haptic feedback in teleoperated systems is crucial, particularly in
applications such as medical, industrial, military, space, underwater, and robot-assisted minimal
invasive surgery (MIS). Appropriate design of haptic interfaces (master robot) and control
algorithms enhance the quality of haptic feedback by addressing objectives such as stability and
transparency. In this thesis, the design and control of telerobotic systems to address these issues are presented. In the first part of the work, a novel haptic device with three degrees of freedom is developed to render touch sensations such as stiffness, texture, shape, and shear concurrently. The developed haptic device is extended to a grasper that provides multi-contact sensations. In addition, a flexure-based backlash-free mechanism is utilized for the power transmission to improve the fidelity. The proposed device is characterized and validated through experiments. In the second part of the work, novel multimodal adaptive robust and RBFNN (Radial basis function-based neural network) based control algorithms for teleoperated systems with time-varying delays have been developed. In addition to the time delay, the most challenging issues that affect haptic feedback are model uncertainties, parametric variations, and external disturbances. The proposed methods ensure robustness against bounded perturbations and high-frequency unmodeled dynamics using a modified sliding-mode controller alongside the adaptive and neural network scheme. The validity of the proposed control laws is substantiated through simulations and experiments.