This paper proposes a mathematical model for an industrial track robot. The model is further used to analyze root cause of track robot vibration. A practical solution is proposed to suppress the vibration. Both simulation and experimental results show that the solution is effective and reliable. Comparisons of the results with existing approaches are also presented. The contributions of this paper include: a) the model abstraction and analysis, which was not reported in the open literature for such track robot system; b) a practical solution first time applied to the track robot system, which results in significant performance improvement in industrial applications

The gene gun is an important apparatus for continuous gene transfection and is widely regarded as a common delivery device for gene therapy. The gene transfer process is a highly dynamics process. To achieve effective treatment, the gene transfer process needs to be well understood and controlled. Unfortunately, no dynamics model is available to analyze the process in the literature. In this paper, a dynamics model of the gene gun is proposed. Based on the mathematical model, simulation studies have been conducted. Relations of penetration depth with helium pressure, acceleration distance, macro-carrier mass, and micro-carrier radius are discussed. The results agree well with experimental results in the literature

This paper describes a Genetic Algorithm (GA) based approach for area coverage using micro-robots. The method can be used for controlled drug delivery or tumor treatment using micro-robots. The algorithm aims to find a near-optimal path that covers a given area entirely, except obstacles defined as biological barriers or drug side effect restricted zones. The proposed GA approach is a dynamic online path planning approach, which is able to achieve planning during motion and to response to detected obstacles. Different from point-to-point path planning, the proposed operators for the GA are specially designed for area coverage. Comparisons of the approach with high-level static optimal search algorithms and low-level fixed path planning approaches are also presented. Simulation results are given to show the effectiveness of the approach.

This paper describes an air pressure sensor based auto-teach/re-teach methodology for industrial multi-link robots. This kind of auto-teach/re-teach function can be easily applied to bio-product manufacturing automation to reduce human-robot interactions. Section 1 introduces the background and objective of auto-teach/re-teach in industrial robotics applications. Section 2 describes the hardware and software of this approach. Section 3 describes the algorithms used in this application. Section 4 shows the user interface and testing result. Section 5 summarizes this approach and indicates the areas for further improvements.