Modeling, Sensor Fusion and Control Techniques in Applied Robotics

Dear Colleagues,

The realization of precise, robust, and intelligent control solutions is based on multiple coordinated design steps in modern robot systems. These design steps include (i) the concrete realization of task-oriented mechatronics systems, (ii) both the derivation and validation of realistic mathematical models, (iii) the calibration of the applied sensor networks, (iv) the estimation of robot states and parameters, and (v) both the design and implementation of intelligent control solutions that provide an energy efficient and robust performance. This Special Issue aims to present novel efficient techniques, which enable the enhancement of overall closed-loop performances in real robot systems (e.g., in mobile robots, UAVs, and robot manipulators). 

Recent research on the below-listed topics is invited. Review papers are also welcome. 

- Optimized mechanics structures in robotic applications, which enable efficient trajectory tracking and translation motion. The analysis can also be extended to vibration diagnostics-based designs, which aim to reduce the levels and patterns of unwanted signals.

- Novel robot modeling and model validation techniques, which provide both relevant and realistic information of real system states. These techniques include novel simulation models and contribute to the obtainment of reliable deductions connected to the behavior of dynamical systems.

- Fusion algorithms of sensor networks for sampling the robot dynamics. These algorithms can include novel filter structures, sensor calibration techniques, and both robust and reliable state estimation methods. Novel measurement solutions that enable the effective derivation of robot states and parameters can also be proposed.

- Novel energy-efficient control solutions that provide a superior performance compared with the conventional methods. Implementation of robust control approaches that handle both the parameter uncertainties/measurement disturbances, and ensure a satisfying control performance.

- Efficient image processing methods that aim to provide the basis for motion planning and reliable trajectory tracking in robot systems.

- Applied industrial solutions in robot systems, which present complex design, implementation, and test results, e.g., artificial intelligence-, IoT-, soft computing-, and/or Industry 4.0-based intelligent robotic solutions in agriculture, construction, medicine, rehabilitation, and biological research. 

Prof. Dr. Jan Awrejcewicz
Dr. Akos Odry
Dr. Peter Odry
Guest Editors

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