Kinematic and dynamic modeling of a robotic head with linear motors

Our present research focuses on kinematic and dynamic modeling of a 3-DOF robotic cutting head for the next generation of CNC machines. The robotic cutting head is one kind of parallel manipulator of 3-PUU type, which has a high flexibility of motion in three-dimensional space. The parallel manipulator consists of three linear servomotors, which drive three connecting rods independently according to the cutting strategy. Being a parallel manipulator, the robotic cutting head has higher stiffness and position accuracy; consequently, higher velocities and accelerations can be achieved. A very suitable application of this mechanism is as a cutting head of a precision machine tool for three-dimensional cutting problems.

Kinematic modeling of a bio-inspired robotic fish

This paper proposes a kinematic modeling method for a bio-inspired robotic fish based on single joint. Lagrangian function of freely swimming robotic fish is built based on a simplified geometric model. In order to build the kinematic model, the fluid force acting on the robotic fish is divided into three parts: the pressure on links, the approach stream pressure and the frictional force. By solving Lagrange's equation of the second kind and the fluid force, the movement of robotic fish is obtained. The robotic fish's motion, such as propelling and turning are simulated, and experiments are taken to verify the model.

Improving the kinematic performance of the SCARA-Tau PKM

One well acknowledged drawback of traditional parallel kinematic machines (PKMs) is that the ratio of accessible workspace to robot footprint is small for these structures. This is most likely a contributing reason why relatively few PKMs are used in industry today. The SCARA-Tau structure is a parallel robot concept designed with the explicit goal of overcoming this limitation and developing a PKM with a workspace similar to that of a serial type robot of the same size. This paper shows for the first time how a proposed variant of the SCARA-Tau PKM can improve the usability of this robot concept further by significantly reducing the dependence between tool platform position and orientation of the original concept. The inverse kinematics of the proposed variant is derived and a comparison is made between this structure and the original SCARA-Tau concept, both with respect to platform orientation changes and workspace.

Is there a link between motor performance variability and social-communicative impairment in children with ADHD-CT : a kinematic study using an upper limb Fitts’ aiming task

 Objective: This study investigated the relationship between motor performance and social-communicative impairment in children with ADHD-combined type (ADHD-CT). Method: An upper limb Fitts’ aiming task was used as a measure of motor performance and the Social Responsiveness Scale as a measure of social-communicative/autistic impairment in the following groups: ADHD-CT (n = 11) and typically developing (TD) controls (n = 10). Results: Children with ADHD-CT displayed greater variability in their movements, reflected in increased error variance over repeated aiming trials compared with TD controls. Motor performance variability was associated with social-communicative deficits in the ADHD-CT but not in the TD group. Conclusion: Social-communicative impairments further complicate the clinical picture of ADHD-CT; therefore, further research in this area is warranted to ascertain whether a particular pattern of motor disturbance in children with ADHD-CT may be clinically useful in identifying and assessing children with a more complex ADHD presentation. © 2012 SAGE Publications.

A novel bio-kinematic encoder for human exercise representation and decomposition - Part 1 : Indexing and modelling

Current bio-kinematic encoders use velocity, acceleration and angular information to encode human exercises. However, in exercise physiology there is a need to distinguish between the shape of the trajectory and its execution dynamics. In this paper we propose such a two-component model and explore how best to compute these components of an action. In particular, we show how a new spatial indexing scheme, derived directly from the underlying differential geometry of curves, provides robust estimates of the shape and dynamics compared to standard temporal indexing schemes.

A novel bio-kinematic encoder for human exercise representation and decomposition - Part 2 : Robustness and Optimisation

Bio-kinematic characterisations of human exercises constitute dealing with parameters such as velocity, acceleration, joint angles, etc. A majority of these are measured directly from various sensors ranging from RGB cameras to inertial sensors. However, due to certain limitations associated with these sensors, such as inherent noise, filters are required to be implemented to subjugate the effect from the noise. When the two-component (trajectory shape and dynamics) bio-kinematic encoding model is being established to represent an exercise, reducing the effect from noise embedded in raw data will be important since the underlying model can be quite sensitive to noise. In this paper, we examine and compare some commonly used filters, namely least-square Gaussian filter, Savitzky-Golay filter and optimal Kalman filter, with four groups of real data collected from Microsoft Kinectc , and assert that Savitzky- Golay filter is the best one when establishing an underlying model for human exercise representation.