The rising interest in collaborative robotics leads to research solutions in order to increase robot interaction with the environment. The development of methods that permit robots to recognize and track human motion is relevant for safety and collaboration matters. A large quantity of data can be measured in real time by Microsoft Kinect®, a well-known low-cost depth sensor, able to recognize human presence and to provide postural information by extrapolating a skeleton. However, the Kinect sensor tracks motion with relatively low accuracy and jerky behavior. For this reason, the effective use in industrial applications in which the measurement of arm velocity is required can be unsuitable. The present work proposes a filtering method that allows the measurement of more accurate velocity values of human arm, based on row data provided by the Kinect sensor. The estimation of arm motion is achieved by a Kalman filter based on a kinematic model and by the imposition of fixed lengths for the skeleton links detected by the sensor. The development of the method is supported by experimental tests. The achieved results suggest the practical applicability of the developed algorithms.
Soft robotics represents a rising trend in recent years, due to the ability to work in unstructured environments or in strict contact with humans. Introducing soft parts, robots can adapt to various contexts overcoming limits relative to the rigid structure of traditional ones. Main issues of soft robotics systems concern the relatively low force exertion and control complexity. Moreover, several fields of application, as space industry, need to develop novel lightweight and deployable robotic systems, that can be stored into a relatively small volume and deployed when required. In this paper, POPUP robot is introduced: a soft manipulator having inflatable links and rigid joints. Its hybrid structure aims to match the advantages of rigid robots and the useful properties of having a lightweight and deployable parts, ensuring simple control, low energy consumption and low compressed gas requirement. The first robot prototype and the system architecture are described highlighting design criteria and effect of internal pressure on the performances. A pseudo-rigid body model is used to describe the behavior of inflatable links looking forward to control design. Finally, the model is extended to the whole robot: multi-body simulations are performed to highlight the importance of suitable sensor equipment for control development, proposing a visual servoing solution.
The rising interest in soft robotics, combined to the increasing applications in the space industry, leads to the development of novel lightweight and deployable robotic systems, that could be easily contained in a relatively small package to be deployed when required. The main challenges for soft robotic systems are the low force exertion and the control complexity. In this manuscript, a soft manipulator concept, having inflatable links, is introduced to face these issues. A prototype of the inflatable link is manufactured and statically characterized using a pseudo-rigid body model on varying inflation pressure. Moreover, the full robot model and algorithms for the load and pose estimation are presented. Finally, a control strategy, using inverse kinematics and an elastostatic approach, is developed. Experimental results provide input data for the control algorithm, and its validity domain is discussed on the basis of a simulation model. This preliminary analysis puts the basis of future advancements in building the robot prototype and developing dynamic models and robust control.
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