Cable compliance

The object of the investigation was to solve mechanical problems using cable-in-bending and cable-in-torsion. These problems included robotic contacts, targets, and controls using cable compliance. Studies continued in the use of cable compliance for the handicapped and the elderly. These included work stations, walkers, prosthetic knee joints, elbow joints, and wrist joints. More than half of these objects were met, and models were made and studies completed on most of the others. It was concluded that the many different and versatile solutions obtained only opened the door to many future challenges

A chewing robot based on parallel mechanism-- analysis and design : a thesis presented in partial fulfilment of the requirements for the degree of Master of Engineering in Mechatronics at Massey University

Masticatory efficiency, dependent on number and condition of the teeth, length of time spent in chewing a bolus and the force exerted when chewing, influences an individual with the selection of food and therefore nutritionally diet. A characterisation of the masticatory efficiency could be possible with a chewing robot that simulates human chewing behaviours in a mechanically controllable way (Pap et al. 2005; Xu et al. 2005). This thesis describes such a chewing robot, developed from a biological basis in terms of jaw structure and muscles of mastication according to published articles. A six degrees of freedom parallel mechanism is proposed with the mandible as a moving platform, the skull as a fixed platform, and six actuators representing the main masticatory muscle groups, temporalis, masseter, and lateral pterygoid on the left and right side. Extensive simulations of inverse kinematics (i.e., generating muscular actuations with implementing recorded human trajectories) were conducted in SolidWorks and COSMOS/Motion to validate two mathematical models of the robot and to analyse kinematic properties. The research showed that selection of appropriate actuation systems, to achieve mandible movement space, velocity, acceleration, and chewing force, was the key challenge in successfully developing a chewing robot. Two custom designed actuation systems, for the six actuators, were developed and built. In the first approach, the muscle groups were presented as linear actuators, positioned so as to reproduce the resultant lines of action of the human muscles. However, with this design concept the spatial requirements specified from the human masticatory system made the physical building of the model impossible. The second approach used a crank mechanism based actuator. This concept did not allow a perfectly linear actuator movement that copied the muscle line of action. However, it was possible to fulfil the spatial requirements set by the human system and to allow reproduction of human chewing behaviours in relation to kinematic requirements and chewing force. The design, manufacture and testing of the entire chewing robot with crank actuators was then carried out. This included the implementation of realistic denture morphology, a mechanical jaw and the framework design for the whole system. In conclusion, this thesis research has developed successfully a mathematical and a physical robotic model. Future work on the control and sensing of the robot and design of a food retention system are required in order to fully functionalise the device

Combining depth and intensity images to produce enhanced object detection for use in a robotic colony

Robotic colonies that can communicate with each other and interact with their ambient environments can be utilized for a wide range of research and industrial applications. However amongst the problems that these colonies face is that of the isolating objects within an environment. Robotic colonies that can isolate objects within the environment can not only map that environment in de-tail, but interact with that ambient space. Many object recognition techniques ex-ist, however these are often complex and computationally expensive, leading to overly complex implementations. In this paper a simple model is proposed to isolate objects, these can then be recognize and tagged. The model will be using 2D and 3D perspectives of the perceptual data to produce a probability map of the outline of an object, therefore addressing the defects that exist with 2D and 3D image techniques. Some of the defects that will be addressed are; low level illumination and objects at similar depths. These issues may not be completely solved, however, the model provided will provide results confident enough for use in a robotic colony