Henrik I. Christensen

Bio: Henrik I. Christensen is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Medicine & Robot. The author has an hindex of 62, co-authored 456 publications receiving 13336 citations. Previous affiliations of Henrik I. Christensen include Herlev Hospital & Technical University of Denmark.

Automatic grasp planning using shape primitives

Abstract: Automatic grasp planning for robotic hands is a difficult problem because of the huge number of possible hand configurations. However, humans simplify the problem by choosing an appropriate prehensile posture appropriate for the object and task to be performed. By modeling an object as a set of shape primitives, such as spheres, cylinders, cones and boxes, we can use a set of rules to generate a set of grasp starting positions and pregrasp shapes that can then be tested on the object model. Each grasp is tested and evaluated within our grasping simulator "GraspIt!", and the best grasps are presented to the user. The simulator can also plan grasps in a complex environment involving obstacles and the reachability constraints of a robot arm.

Computational visual attention systems and their cognitive foundations: A survey

Abstract: Based on concepts of the human visual system, computational visual attention systems aim to detect regions of interest in images. Psychologists, neurobiologists, and computer scientists have investigated visual attention thoroughly during the last decades and profited considerably from each other. However, the interdisciplinarity of the topic holds not only benefits but also difficulties: Concepts of other fields are usually hard to access due to differences in vocabulary and lack of knowledge of the relevant literature. This article aims to bridge this gap and bring together concepts and ideas from the different research areas. It provides an extensive survey of the grounding psychological and biological research on visual attention as well as the current state of the art of computational systems. Furthermore, it presents a broad range of applications of computational attention systems in fields like computer vision, cognitive systems, and mobile robotics. We conclude with a discussion on the limitations and open questions in the field.

Combating COVID-19-The role of robotics in managing public health and infectious diseases.

Abstract: COVID-19 may drive sustained research in robotics to address risks of infectious diseases. COVID-19 may drive sustained research in robotics to address risks of infectious diseases.

Restricting volumes of resuscitation fluid in adults with septic shock after initial management: the CLASSIC randomised, parallel-group, multicentre feasibility trial

Abstract: We assessed the effects of a protocol restricting resuscitation fluid vs. a standard care protocol after initial resuscitation in intensive care unit (ICU) patients with septic shock. We randomised 151 adult patients with septic shock who had received initial fluid resuscitation in nine Scandinavian ICUs. In the fluid restriction group fluid boluses were permitted only if signs of severe hypoperfusion occurred, while in the standard care group fluid boluses were permitted as long as circulation continued to improve. The co-primary outcome measures, resuscitation fluid volumes at day 5 and during ICU stay, were lower in the fluid restriction group than in the standard care group [mean differences −1.2 L (95 % confidence interval −2.0 to −0.4); p < 0.001 and −1.4 L (−2.4 to −0.4) respectively; p < 0.001]. Neither total fluid inputs and balances nor serious adverse reactions differed statistically significantly between the groups. Major protocol violations occurred in 27/75 patients in the fluid restriction group. Ischaemic events occurred in 3/75 in the fluid restriction group vs. 9/76 in the standard care group (odds ratio 0.32; 0.08–1.27; p = 0.11), worsening of acute kidney injury in 27/73 vs. 39/72 (0.46; 0.23–0.92; p = 0.03), and death by 90 days in 25/75 vs. 31/76 (0.71; 0.36–1.40; p = 0.32). A protocol restricting resuscitation fluid successfully reduced volumes of resuscitation fluid compared with a standard care protocol in adult ICU patients with septic shock. The patient-centred outcomes all pointed towards benefit with fluid restriction, but our trial was not powered to show differences in these exploratory outcomes. NCT02079402.

"My Roomba is Rambo": intimate home appliances

Abstract: Robots have entered our domestic lives, but yet, little is known about their impact on the home. This paper takes steps towards addressing this omission, by reporting results from an empirical study of iRobot's Roomba™, a vacuuming robot. Our findings suggest that, by developing intimacy to the robot, our participants were able to derive increased pleasure from cleaning, and expended effort to fit Roomba into their homes, and shared it with others. These findings lead us to propose four design implications that we argue could increase people's enthusiasm for smart home technologies.

Pattern Recognition and Machine Learning

Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Planning Algorithms: Introductory Material

Abstract: Planning algorithms are impacting technical disciplines and industries around the world, including robotics, computer-aided design, manufacturing, computer graphics, aerospace applications, drug design, and protein folding. This coherent and comprehensive book unifies material from several sources, including robotics, control theory, artificial intelligence, and algorithms. The treatment is centered on robot motion planning but integrates material on planning in discrete spaces. A major part of the book is devoted to planning under uncertainty, including decision theory, Markov decision processes, and information spaces, which are the “configuration spaces” of all sensor-based planning problems. The last part of the book delves into planning under differential constraints that arise when automating the motions of virtually any mechanical system. Developed from courses taught by the author, the book is intended for students, engineers, and researchers in robotics, artificial intelligence, and control theory as well as computer graphics, algorithms, and computational biology.

A review of feature selection techniques in bioinformatics

Abstract: Feature selection techniques have become an apparent need in many bioinformatics applications. In addition to the large pool of techniques that have already been developed in the machine learning and data mining fields, specific applications in bioinformatics have led to a wealth of newly proposed techniques. In this article, we make the interested reader aware of the possibilities of feature selection, providing a basic taxonomy of feature selection techniques, and discussing their use, variety and potential in a number of both common as well as upcoming bioinformatics applications. Contact: yvan.saeys@psb.ugent.be Supplementary information: http://bioinformatics.psb.ugent.be/supplementary_data/yvsae/fsreview

Simultaneous localization and mapping: part I

Abstract: This paper describes the simultaneous localization and mapping (SLAM) problem and the essential methods for solving the SLAM problem and summarizes key implementations and demonstrations of the method. While there are still many practical issues to overcome, especially in more complex outdoor environments, the general SLAM method is now a well understood and established part of robotics. Another part of the tutorial summarized more recent works in addressing some of the remaining issues in SLAM, including computation, feature representation, and data association