Dugan Um

A modularized sensitive skin for motion planning in uncertain environments

One way to avoid obstacles without modeling the environment is to use a sensor-based sensitive skin covering the body of the robot along with proper sensor-based motion planning algorithms. Compared to prior attempts, the system developed at the UW-Madison Robotics Lab and discussed here presents a system that can be easily reconfigured for a variety of applications. This is accomplished via modularized sensitive skin patches that can be connected in various ways, and a hierarchical control architecture that can be easily modified for various system configurations. In the implemented version, the skin contains about 1000 infrared sensors; it can be easily expanded, with minor changes. The system has been successfully tested in preliminary trials.

T-less : A novel touchless human-machine interface based on infrared proximity sensing

In todays industry, intuitive gesture recognition, as manifested in numerous consumer electronics devices, becomes a main issue of HMI device research. Although finger-tip touch based user interface has paved a main stream in mobile electronics, we envision touch-less HMI as a promising technology in futuristic applications with higher potential in areas where sanity or outdoor operation become of importance. In this paper, we introduce a novel HMI device for non-contact gesture input for intuitive HMI experiences. The enabling technology of the proposed device is the IPA (infrared Proximity Array) sensor by which realtime 3 dimensional depth information can be captured and realized for machine control. For the usability study, two different operating modes are adopted for hand motion inputs: one is a finger tip control mode and the other is a palm control mode. Throughput of the proposed device has been studied and compared to a traditional mouse device for usability evaluation. During the human subject test, the proposed device is found to be useful for PC mouse pointer control. The experimental results are shared in the paper as well.

Fault tolerance via analytic redundancy for a modularized sensitive skin

As sensor arrays become ever larger in complex automation systems, provisions for sensor fault detection and tolerance become mandatory. This work addresses the question of real-time fault tolerance in large two-dimensional sensor arrays, with the number of sensors on the order of thousands or more. As an example, we consider a flexible sensitive skin system with uniformly distributed infrared sensors. The purpose of the skin is to cover the whole body of a mobile robot or a robot arm manipulator, and serve as a front end of a motion planning and collision avoidance system. The goal of the proposed approach to fault tolerance is to maintain machines functionality in situations with damaged sensors; without it, erroneous motion or collisions with surrounding objects would occur. The approach makes use of analytic redundancy whereby periodical comparison is made of sensor measurements with dynamically adjusted expected values of sensor readings. Two fault tolerance schemes, online and off-line, are considered. The properties of both schemes are analyzed and results of experiments demonstrating their performance are discussed.

Fault tolerance via component redundancy for a modularized sensitive skin

The objective of this work is to develop a fault tolerant system for a sensitive skin-based motion planning system. The purpose of the skin is to provide real-time collision avoidance for a machine (e.g. a mobile robot or an arm manipulator) operating in an uncertain environment with obstacles. The skin is designed to cover virtually any kind of machine; in the version used in this project the skin covers an industrial arm manipulator and contains about 1000 infrared sensors. In order to operate such a complex system in real time, effective fault tolerance is necessary. The latter is achieved in our system via component redundancy: the distance measurements necessary for motion planning are done using a particular scheme for sensor grouping. The system achieves safe motion planning even if some of the sensors are dead or partially inoperative. Based on the fault tolerance model used a fault tolerance algorithm is developed, tested and demonstrated experimentally.

Simultaneous planning and mapping (SPAM) for a manipulator by best next move in unknown environments

In this paper, we propose a SPAM (Simultaneous Planning and Mapping) technique for a manipulator type robot working in an uncertain environment via a Best Next Move algorithm. Demands for a smart decision to move a manipulator such as humanoid arms in uncertain or crowded environments call for a simultaneous planning and mapping technique. We assume no a priori knowledge of either the obstacles or the rest of the environment exits. For rapid map building and path planning, we use a skin type setup based on 3D depth camera sensors that completely encompass the entire body of a manipulator. The 3D sensors capture the point clouds used to create an instantaneous c-space map whereby a Best Next Move algorithm directs the motion of the manipulator. The Best Next Move algorithm utilizes the gradient of the density distribution of the k-nearest-neighborhood sets in c-space. It has tendency to travel along the direction by which the point clouds spread in space, thus rendering faster mapping of c-space obstacles. The proposed algorithm is compared with several sensor based algorithms for performance measurement such as map completion rate, distribution of samples, total nodes, etc. Some improved performances are reported for the proposed algorithm. Several possible applications include semi-autonomous tele-robotics planning, humanoid arm path planning, among others.

Micro scale silicon dioxide gear fabrication by bulk micromachining process

The purpose of this research was to find a cost effective and repeatable method for releasing high-quality micro-parts from a silicon substrate by bulk micromachining technology. Crystallographic shape removal technology on the finally released silicon oxide parts was put into scrutiny. Several methods were approached as possible solutions. These methods include ethylenediamine — pyrocatechol — water (EPW) etchant, the addition of a boron dopant to the silicon dioxide layer, pre-thinning of wafers, and the use of polyimide coatings to thin the silicon substrate subsequent to part release. The combined method of boron doping and polyimide coating produced the best results.

Model-based micro profile measurement using multi-focused images for micro gear assembly

A novel model based 3D depth measurement technology for micro parts is introduced in this paper. Unlike chemically released parts and assembled integrity by MEMS technology, micro assembly is still a daunting task due to difficulties in parts visualization and assembly autonomy. Conformal mapping has gained popularity due to its usefulness for depth measure in micro parts of the size of human hairs. The processing time to obtain 10 to 100 photos for each pixel and expensive device value, though, hinder commercialization for various micro application industries. In this research, we investigate a novel model based 3D depth measurement technology for faster and cost effective means to promote micro assembly technology in various application fields. Micro parts, by its nature, are known of its shape in advance for the majority of micro applications. We take advantage of the previously known shape of micro parts and hence apply model based approach for a faster and cost effective 3D depth measure. The proposed 3D depth measuring method is based on pattern recognition and multi-focus technique enabling it to extract only information useful for micro parts assembly such as location, size, and height of a micro part. For demonstration purpose, micro gears are fabricated by bulk micro machining technology. In addition, a functioning micro assembly system is developed and used to prove the usefulness of the proposed 3D depth measurement technology.

A FLEXIBLE MICRO MANUFACTURING SYSTEM FOR MICRO PARTS ASSEMBLY VIA MICRO VISUAL SENSING AND EAP BASED GRASPING

In this paper, we developed a flexible micro workcell for micro part assembly and bio materials handling. The primary focus of the research is on the flexible manufacturing system that can handle parts in the size of 100 to 500 μm for various applications. Flexibility in micro assembly, though important, has not been examined in depth due to the complexity of micro operations of small parts. Micro gears, micro glass fibers or fragile bio materials require flexibility in gripping and haptic feedback control for further operation. To that end, we design grippers made out of electro active polymer, controlled by high precision micro manipulator for a novel micro assembly process, namely flexible micro assembly system (FMAS). The areas of research include micro/nano electro-mechanical system (MEMS) material and structure, micro sensor/actuator system, visual feedback control system, micro-robotic arm motion control and flexible micro-gripper system. In order to verify the functional aspect of the FMAS, we made micro mechanical gears fabricated via bulk micromachining technology for 3D micro vision capability and handling precision of micro robotic manipulator.

3D Geometric Modeling

This chapter summarizes the concept of 3D modeling. In more detail, it covers coordinate transformation for translation and rotation between frames. In addition, several 3D modeling schemes are discussed.

Finite Element Modeling and Analysis

This chapter summarizes the basic principles of Finite Element Modeling and Analysis. In more detail, it covers truss principle, mesh generation, governing equation development, and stiffness method for meshed solid analysis.