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Rapid robotic system development sets a demand for multi-disciplinary methods and tools to explore and compare design alternatives. In this paper, we present collaborative modeling that combines discrete-event models of controller software with continuous-time models of physical robot components. The presented co-modeling method utilized VDM for discrete-event and 20-sim for continuous-time modeling. The collaborative modeling method is illustrated with a concrete example of collaborative model development of a mobile robot animal feeding system. Simulations are used to evaluate the robot model output response in relation to operational demands. The result of the simulations provides the developers with an overview of the impacts of each solution instance in the chosen design space. Based on the solution overview the developers can select candidates that are deemed viable to be deployed and tested on an actual physical robot.
Many robot control scenarios involve assessing system robustness against a task specification. If either the controller or environment are composed of black-box components with unknown dynamics, we cannot rely on formal verification to assess our sys
This work introduces an approach for automatic hair combing by a lightweight robot. For people living with limited mobility, dexterity, or chronic fatigue, combing hair is often a difficult task that negatively impacts personal routines. We propose a
Tactile sensing plays an important role in robotic perception and manipulation. To overcome the real-world limitations of data collection, simulating tactile response in virtual environment comes as a desire direction of robotic research. Most existi
Robotic cutting of soft materials is critical for applications such as food processing, household automation, and surgical manipulation. As in other areas of robotics, simulators can facilitate controller verification, policy learning, and dataset ge
Physically-realistic simulated environments are powerful platforms for enabling measurable, replicable and statistically-robust investigation of complex robotic systems. Such environments are epitomised by the RoboCup simulation leagues, which have b