Using the novel actuators electrostatic actuators and electrodense films (instead of conventional motors and magnets) for actuation and latching respectively, we build ultra-thin (2.5 mm high), flexible (no rigid component) climbing robots (distinguished them from the conventional rigid clumsy climbing robots), which can be applied to the inspection in a narrow gap or confined space.
Multiple-segment flexible and soft robotic arms composed by ionic polymer–metal composite (IPMC) flexible actuators exhibit compliance but suffer from the difficulty of path planning due to their redundant degrees of freedom, although they are promising in complex tasks such as crossing body cavities to grasp objects. We propose a learning from demonstration method to plan the motion paths of IPMC based manipulators, by statistics machine-learning algorithms. To encode demonstrated trajectories and estimate suitable paths for the manipulators to reproduce the task, models are built based on Gaussian Mixture Model and Gaussian Mixture Regression respectively. The forward and inverse kinematic models of IPMC based soft robotic arm are derived for the motion control. A flexible and soft robotic manipulator is implemented with six IPMC segments, and it verifies the learned paths by successfully completing a representative task of navigating through a narrow keyhole.
Traditional rigid robotic hand manipulator has been used in many field nowadays due to its advantages of large gripping force and stable performance. However, this kind of rigid manipulator is not suitable for gripping fragile objects since it is motorized and force control can be a problem. It is also not suitable to grip object with different shapes since the manipulator is rigid and not compliant. In this study, a novel manipulator with gripping capability is designed and fabricated. The manipulator combines electrostatic adhesion actuation with soft manipulators. The manipulator has high flexibility and can be compliant to different shapes due to the property of the materials. It is very promising to do delicate manipulations in industry field and biomedical field.
- Built a model for localization and tracking of multiple sound sources
- Designed and fabricated the mechanical structures and the circuit of microphone arrays for sound-source localization and tracking
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