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Auflistung Künstliche Intelligenz 33(4) - Dezember 2019 nach Titel
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- ZeitschriftenartikelA Philosophically Motivated View on AI and Robotics(KI - Künstliche Intelligenz: Vol. 33, No. 4, 2019) Kunze, Lars; Sloman, Aaron
- ZeitschriftenartikelAn Introduction to Hyperdimensional Computing for Robotics(KI - Künstliche Intelligenz: Vol. 33, No. 4, 2019) Neubert, Peer; Schubert, Stefan; Protzel, PeterHyperdimensional computing combines very high-dimensional vector spaces (e.g. 10,000 dimensional) with a set of carefully designed operators to perform symbolic computations with large numerical vectors. The goal is to exploit their representational power and noise robustness for a broad range of computational tasks. Although there are surprising and impressive results in the literature, the application to practical problems in the area of robotics is so far very limited. In this work, we aim at providing an easy to access introduction to the underlying mathematical concepts and describe the existing computational implementations in form of vector symbolic architectures (VSAs). This is accompanied by references to existing applications of VSAs in the literature. To bridge the gap to practical applications, we describe and experimentally demonstrate the application of VSAs to three different robotic tasks: viewpoint invariant object recognition, place recognition and learning of simple reactive behaviors. The paper closes with a discussion of current limitations and open questions.
- ZeitschriftenartikelBenchmarking Functionalities of Domestic Service Robots Through Scientific Competitions(KI - Künstliche Intelligenz: Vol. 33, No. 4, 2019) Basiri, Meysam; Piazza, Enrico; Matteucci, Matteo; Lima, PedroBenchmarking via carefully designed competitions makes it possible to provide a common framework for the rigorous comparison of intelligent and autonomous systems; competitions may play the role of scientific experiments while being appealing both to researchers and to the general public thus promoting critical analysis of systems outside the labs. This paper describes our approach to benchmarking domestic service robots through organizing recurrent competitions under the European Robotics League. It details the tools and benchmarks designed to evaluate the performance of robots at task and functionality levels. In particular, the functionality benchmarks for object perception and navigation are described and an overview of the new benchmarks to appear in the league is presented.
- ZeitschriftenartikelCategorisations: AI(KI - Künstliche Intelligenz: Vol. 33, No. 4, 2019) Timpf, Sabine
- ZeitschriftenartikelDeskilling Robots in Logistics Environments(KI - Künstliche Intelligenz: Vol. 33, No. 4, 2019) Davies, Martin RaymondRobots are installed in logistics environments because they are adaptive; unlike their rigid mechanized counterparts, e.g. conveyors and lifts. Maintaining this adaptability post installation; and leaving it to the customer to reconfigure and maintain the system is still a difficult proposal. Deskilling the introduction and sustainability of robotic systems therefore is a key success factor for replacing traditional static capital equipment.
- ZeitschriftenartikelEfficient Supervision for Robot Learning Via Imitation, Simulation, and Adaptation(KI - Künstliche Intelligenz: Vol. 33, No. 4, 2019) Wulfmeier, MarkusRecent successes in machine learning have led to a shift in the design of autonomous systems, improving performance on existing tasks and rendering new applications possible. Data-focused approaches gain relevance across diverse, intricate applications when developing data collection and curation pipelines becomes more effective than manual behaviour design. The following work aims at increasing the efficiency of this pipeline in two principal ways: by utilising more powerful sources of informative data and by extracting additional information from existing data. In particular, we target three orthogonal fronts: imitation learning, domain adaptation, and transfer from simulation.
- ZeitschriftenartikelNews(KI - Künstliche Intelligenz: Vol. 33, No. 4, 2019)
- ZeitschriftenartikelOn the Applicability of Probabilistic Programming Languages for Causal Activity Recognition(KI - Künstliche Intelligenz: Vol. 33, No. 4, 2019) Lüdtke, Stefan; Popko, Maximilian; Kirste, ThomasRecognizing causal activities of human protagonists, and jointly inferring context information like location of objects and agents from noisy sensor data is a challenging task. Causal models can be used, which describe the activity structure symbolically, e.g. by precondition-effect actions. Recently, probabilistic programming languages (PPLs) arose as an abstraction mechanism that allow to concisely define probabilistic models by a general-purpose programming language, and provide off-the-shelf, general-purpose inference algorithms. In this paper, we empirically investigate whether PPLs provide a feasible alternative for implementing causal models for human activity recognition, by comparing the performance of three different PPLs (Anglican, WebPPL and Figaro) on a multi-agent scenario. We find that PPLs allow to concisely express causal models, but general-purpose inference algorithms that are typically implemented in PPLs are outperformed by an application-specific inference algorithm by orders of magnitude. Still, PPLs can be a valuable tool for developing probabilistic models, due to their expressiveness and simple applicability.
- ZeitschriftenartikelReg3DFacePtCd: Registration of 3D Point Clouds Using a Common Set of Landmarks for Alignment of Human Face Images(KI - Künstliche Intelligenz: Vol. 33, No. 4, 2019) Bagchi, Parama; Bhattacharjee, Debotosh; Nasipuri, MitaThe present work proposes a new method Reg3DFacePtCd for registration of point clouds. The key contribution of the present method is that an unknown face in 3D point cloud form is given to the system and is registered to the already existing known 3D face point clouds using a fast 3D face registration method. The novelty of the present technique is that at first the alignment and registration parameters are found out by initially registering eight key points of the unknown source model to that of the known model. Next, the rest of the point clouds of the unknown model are registered to that of the known model using the same parameters found as above. The main method used for alignment is iterative closest point (ICP) using point-based technique followed by registration in the least squares sense. Mainly there are two significant contributions. Firstly, we have developed a new mathematical model facial landmark point based model across poses to obtain the target or the known model to which all the unknown models will be registered. Secondly, a novel way to accelerate point cloud matching by reducing the number of points has been proposed. Using a small number of points necessarily would speed up the registration process but may inculcate errors. So, to determine the registration quality of the fundamental eight key points on which the entire registration process is based, a new robust metric namely ICV (ICP certainty vector) consisting of several key components have been used. Finally, we have addressed several important face registration issues like pre-processing, convergence and quality of registration of the entire facial point cloud based on the eight key points. Extensive experimentation on Frav3D, GavabDB, and the Bosphorus databases on a high-performance computing environment show the novelty and robustness of the method.
- ZeitschriftenartikelShakey Ever After? Questioning Tacit Assumptions in Robotics and Artificial Intelligence(KI - Künstliche Intelligenz: Vol. 33, No. 4, 2019) Kirsch, AlexandraShakey the robot was a milestone of autonomous robots and artificial intelligence. Its design principles have dominated research until now. Tacit philosophical and architectural assumptions have impoverished the space of research topics and methods. I point out ways to overcome this impasse with sideglances to other scientific fields.