CISR Research Seminar Series - 2009

 Abstract

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.

 Abstract

Having some level of a-priori information about an object is very useful when detecting and estimating its pose in real-time systems, i.e. augmented reality. A-priori information generated from training data must accurately represent distinctive and repeatable object features, and be robust to scaling, illumination and perspective distortion. This talk will outline current work in developing a algorithm to generate a distinctive object representation offline, using short baseline stereo fundamentals to triangulate highly descriptive object features in multiple pairs of stereo images. When a set of sparse 2.5D perspective views are built, the multiple pairs are then fused into a single sparse 3D model using a common 3D shape registration technique.

 Abstract

Discovering knowledge in measured data is very important for us to determine data input model for modelling and predicating passengers and handbags at a specific section of airport. The unique technique - SOM (Self-Organising Map) will be introduced to classify and visualise raw data collected from different sections of airport, such performance is useful for us to gain prior information from raw data for selecting candidate model. Based on obtained prior information and experience of selecting suitable parametrical model for predication, the challenging technique - inverse problem theory will afterward be introduced for estimating values of parameters of candidate model and eventually confirming data input model with higher accuracy. Meanwhile, some detailed examples of how to solve cases of engineering or science using SOM and inverse problem theory will be represented as an approach to further research in this field.

 Abstract

Mission and path planning for multiple robots in dynamic environments are required when multiple robot or UVs (UAVs, GUVs, UUVs) are used and a group of targets needs to be done. The problem is critical for most multi cooperative robots in dynamic environment as an instance a group of rescue robots or UAVs for rescue needs mission and path planning. This problem is a complex decision making problems which includes different uncertain environmental, obstacles and robotic issues. In this study different cases of the problem have been solved and will be introduced and the most complex form will be discussed. In this form more over than potential field concept the priority for robots, targets are considered by introducing suitable weighting coefficients. Uncertainty in movement and threatening concept has been used for obstacles. Finally the solution will be presented by a simulation in dynamic way, means for every run because of properties of dynamic environments and inherent uncertainties, the provided result will be different. To show how this method can be used under various optimality conditions, we developed region priority concept for robot movements which will be indicated.