Vision technology/algorithms for space robotics applications

The thrust of automation and robotics for space applications has been proposed for increased productivity, improved reliability, increased flexibility, higher safety, and for the performance of automating time-consuming tasks, increasing productivity/performance of crew-accomplished tasks, and performing tasks beyond the capability of the crew. This paper provides a review of efforts currently in progress in the area of robotic vision. Both systems and algorithms are discussed. The evolution of future vision/sensing is projected to include the fusion of multisensors ranging from microwave to optical with multimode capability to include position, attitude, recognition, and motion parameters. The key feature of the overall system design will be small size and weight, fast signal processing, robust algorithms, and accurate parameter determination. These aspects of vision/sensing are also discussed

Optical techniques for 3D surface reconstruction in computer-assisted laparoscopic surgery

One of the main challenges for computer-assisted surgery (CAS) is to determine the intra-opera- tive morphology and motion of soft-tissues. This information is prerequisite to the registration of multi-modal patient-specific data for enhancing the surgeon’s navigation capabilites by observ- ing beyond exposed tissue surfaces and for providing intelligent control of robotic-assisted in- struments. In minimally invasive surgery (MIS), optical techniques are an increasingly attractive approach for in vivo 3D reconstruction of the soft-tissue surface geometry. This paper reviews the state-of-the-art methods for optical intra-operative 3D reconstruction in laparoscopic surgery and discusses the technical challenges and future perspectives towards clinical translation. With the recent paradigm shift of surgical practice towards MIS and new developments in 3D opti- cal imaging, this is a timely discussion about technologies that could facilitate complex CAS procedures in dynamic and deformable anatomical regions

Proceedings of the 2009 Joint Workshop of Fraunhofer IOSB and Institute for Anthropomatics, Vision and Fusion Laboratory

The joint workshop of the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB, Karlsruhe, and the Vision and Fusion Laboratory (Institute for Anthropomatics, Karlsruhe Institute of Technology (KIT)), is organized annually since 2005 with the aim to report on the latest research and development findings of the doctoral students of both institutions. This book provides a collection of 16 technical reports on the research results presented on the 2009 workshop

Doctor of Philosophy

dissertationThree-dimensional (3D) models of industrial plant primitives are used extensively in modern asset design, management, and visualization systems. Such systems allow users to efficiently perform tasks in Computer Aided Design (CAD), life-cycle management, construction progress monitoring, virtual reality training, marketing walk-throughs, or other visualization. Thus, capturing industrial plant models has correspondingly become a rapidly growing industry. The purpose of this research was to demonstrate an efficient way to ascertain physical model parameters of reflectance properties of industrial plant primitives for use in CAD and 3D modeling visualization systems. The first part of this research outlines the sources of error corresponding to 3D models created from Light Detection and Ranging (LiDAR) point clouds. Fourier analysis exposes the error due to a LiDAR system's finite sampling rate. Taylor expansion illustrates the errors associated with linearization due to flat polygonal surfaces. Finally, a statistical analysis of the error associated with LiDar scanner hardware is presented. The second part of this research demonstrates a method for determining Phong specular and Oren-Nayar diffuse reflectance parameters for modeling and rendering pipes, the most ubiquitous form of industrial plant primitives. For specular reflectance, the Phong model is used. Estimates of specular and diffuse parameters of two ideal cylinders and one measured cylinder using brightness data acquired from a LiDAR scanner are presented. The estimated reflectance model of the measured cylinder has a mean relative error of 2.88% and a standard deviation of relative error of 4.0%. The final part of this research describes a method for determining specular, diffuse and color material properties and applies the method to seven pipes from an industrial plant. The colorless specular and diffuse properties were estimated by numerically inverting LiDAR brightness data. The color ambient and diffuse properties are estimated using k-means clustering. The colorless properties yielded estimated brightness values that are within an RMS of 3.4% with a maximum of 7.0% and a minimum of 1.6%. The estimated color properties effected an RMS residual of 13.2% with a maximum of 20.3% and a minimum of 9.1%