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PLANNING OF SENSING TASKS IN AN ASSEMBLY ENVIRONMENT

JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 1991年第3期4卷 221-254页

作者： WERLING, G 1. Institute for Real-Time Computer Control Systems and Robotics University of Karlsruhe D-7500 Karlsruhe Germany

The purpose of this paper is to give an overview of past and recent work on planning sensing strategies for vision sensors. To achieve an economic use of robots in manufacturing, their programs must provide a high degree of fault-tolerance, security, and robustness to prevent unforeseen errors. Model errors (also termed uncertainties) are one of the most frequent reasons for such undesirable events. Robot systems can be made more reliable and fault-tolerant by providing them with capabilities of error detection and recovery, or error prevention. The latter may be achieved by reducing model errors using tactile and non-tactile sensors. The quality of a robot program synthesized by a task-level programming system depends on the accuracy of the model, since all information that is not explicitly given by the programmer must be derived from it. This means that the following questions have to be answered by the automatic task planner in order to plan non-tactile sensing strategies: (1) When do I have to use sensors to reduce uncertainty about the real world? (2) What do I have to use them for? (3) How do I have to use them to achieve the necessary information within an acceptable period of time? There are very few systems which deal broadly with the problem of robust robot programs, whereas there are numerous works on detail aspects of the field. The main approaches will be introduced and discussed in more detail. Finally, a new concept for generating sensor-integrated robust robot programs will be proposed.

关键词： VERIFICATION TASK-LEVEL PROGRAMMING ROBOT VISION UNCERTAINTY ASSEMBLY PLANNING FAULT TOLERANCE CLASSIFICATION PREDICTION CAMERA LOCATION

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A programming and simulation environment for the karlsruhe dextrous hand

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robotics and Autonomous Systems 1990年第3期6卷 243-263页

作者： Wöhlke, G. Institute for Real-Time Computer Control and Robotics Faculty for Informatics University of Karlsruhe Karlsruhe7500 Germany

In this paper the development of a programming and simulation environment is described, which was especially tailored for programming of multifinger hands. The research has concerned with the programming of the Karlsruhe Dextrous Hand, a non-anthropomorphic three finger gripper with 9 degrees of freedom, which is being developed at our institute. The work presents the results of a task-oriented approach to the object manipulation problem and contains two main parts: a system programming module and an application programming module. This realization supports the interactive generation and evaluation of a hand program using graphical simulation. © 1990 Elsevier Science Publishers B.V.

关键词： Degrees of freedom (mechanics)

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A concept for an intelligent and fault-tolerant robot system

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Journal of Intelligent and Robotic Systems 1988年第3期1卷 259-286页

作者： Hörmann, A. Hugel, Th. Meier, W. Institute for Real-Time Computer Control Systems and Robotics Faculty of Informatics University of Karlsruhe Karlsruhe Germany

A concept for the intelligent control of subsystems of a flexible assembly cell is presented. Unknown or uncertain data about the real world may lead towards failure during an assembly task. Therefore, a fault tolerant system must be capable of reacting immediately to error situations. Thus, the major topic of this paper is the dynamic handling of unforeseen situations during realtime activities. This will be achieved by combining sensor guided actions with an advanced autonomous supervision system. Experimental results will be derived from the mobile two-arm robot system KAMRO of the institute for real-time Computer control Systems and robotics, University of Karlsruhe, Federal Republic of Germany. © 1988 Kluwer Academic Publishers.

关键词： Computer control systems

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AN ACTION-BASED process MODEL FOR DEXTEROUS MULTIFINGER HANDS

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 1991年第3期4卷 201-219页

作者： WOHLKE, G BRAUN, T 1. Institute for Real-Time Computer Control Systems and Robotics Faculty for Informatics University of Karlsruhe 7500 Karlsruhe Germany

In this article, the development of an action-based process model is described which was especially tailored to the needs of modelling and simulating multifinger hands. The research has been concerned with a description technique using constraints for modelling the working environment and with the design of an appropriate process model for simulating complex movements of manipulation objects with multifinger hands. The paper presents the results of an object-oriented approach to the proposed model and consists of two parts: a constraint net that describes the connections and relations between cell components (robots, grippers, objects) in the working environment and a propagation algorithm that computes the new locations regarding the modifications and logical dependencies.

关键词： SYSTEM SIMULATION process MODEL CONSTRAINT NET PROPAGATION ALGORITHM OBJECT-ORIENTED PROGRAMMING

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THE control ARCHITECTURE OF THE PRIAMOS MOBILE SYSTEM

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control ENGINEERING PRACTICE 1994年第2期2卷 341-346页

作者： DILLMANN, R KREUZIGER, J WALLNER, F Department of Computer Science University of Karlsruhe Institute for Real-Time Computer Control Systems and Robotics P.O. Box 6980 76128 Karlsruhe Germany

In this paper the control architecture of the PRIAMOS mobile robot system is presented. It consists of four layers which integrate reactive and reflexive components in such a way that the robot can combine fast reaction to unexpected obstacles with predictive behaviour to known components in the environment. A solution for the problem of how to combine control layers which process information on different levels of abstraction and of increasing complexity is discussed. The reflexive part of the control architecture and the modification concerning the motion controller of the mobile robot which was necessary to apply the idea of reflexive navigation is described in more detail. The architecture presented allows motion tasks to be executed in partially unknown or changing environment in an efficient manner. Especially, the time-critical reflexive level is computationally less expensive than in previous approaches.

关键词： INTELLIGENT MACHINES NAVIGATION HIERARCHICALLY INTELLIGENT control ARCHITECTURE OBSTACLE AVOIDANCE ROBOTS SENSORS

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A system for robot assisted maxillofacial surgery

A system for robot assisted maxillofacial surgery

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6th Conferenc on Medicine Meets Virtual reality, MMVR 1998

作者： Burghart, Catherina R. Muenchenberg, Jan E. Rembold, Ulrich Institute of Real-Time Computer Control Systems and Robotics University of Karlsruhe 76128 Karlsruhe Germany

ISBN: (纸本)9051993862

In maxillofacial surgery the quality of the surgical outcome mainly depends on the experience of the operating surgeon. Thus we intend to support the surgeon before and during surgery in order to enhance the surgical results. On the one hand this implies the use of image processing, three dimensional modelling techniques and visualization techniques of medical image data, on the other hand planning systems, intraoperative navigation devices and surgical robots are needed. In this paper a complex expert system is presented, which uses a planner for generating treatment plans, an infrared navigation for monitoring both patient, robot, and surgical tool, and a surgical robotic system in order to work on bone. Special stress is laid on the architecture of the planning system, the structure of the treatment plans, and the intraopertative communication protocols.

关键词： Robotic surgery

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Knowledgebased segmentation

Knowledgebased segmentation

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6th Conferenc on Medicine Meets Virtual reality, MMVR 1998

作者： Burghart, Catherina R. Pernozzoli, Arno Rembold, Ulrich Institute of Real-Time Computer Control Systems and Robotics University of Karlsruhe 76128 Karlsruhe Germany

ISBN: (纸本)9051993862

The segmentation of medical images like CT or MRI scans represents a great challenge to researchers in computer vision, due to the variability of the individual anatomy and the different characteristics of the scanning systems. As an anatomical knowledge base improves the recognition of structures in CT or MRI scans, we chose a knowledge based segmentation in our approach, which will be explained in the following.

关键词： Computerized tomography

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Genetic Informed Trees (GIT*): Path planning via reinforced genetic programming heuristics

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Biomimetic Intelligence and robotics 2025年

作者： Liding Zhang Kuanqi Cai Zhenshan Bing Chaoqun Wang Alois Knoll Chair of Robotics Artificial Intelligence and Real-time Systems TUM School of Computation Information and Technology (CIT) Technical University of Munich Munich 85748 Germany Chair of Robotics and Systems Intelligence Munich Institute of Robotics and Machine Intelligence (MIRMI) Technical University of Munich Munich 80992 Germany School of Control Science and Engineering Shandong University Jinan 250100 China

Optimal path planning involves finding a feasible state sequence between a start and a goal that optimizes an objective. This process relies on heuristic functions to guide the search direction. While a robust function can improve search efficiency and solution quality, current methods often overlook available environmental data and simplify the function structure due to the complexity of information relationships. This study introduces Genetic Informed Trees (GIT*), which improves upon Effort Informed Trees (EIT*) by integrating a wider array of environmental data, such as repulsive forces from obstacles and the dynamic importance of vertices, to refine heuristic functions for better guidance. Furthermore, we integrated reinforced genetic programming (RGP), which combines genetic programming with reward system feedback to mutate genotype-generative heuristic functions for GIT*. RGP leverages a multitude of data types, thereby improving computational efficiency and solution quality within a set timeframe. Comparative analyses demonstrate that GIT* surpasses existing single-query, sampling-based planners in problems ranging from R 4 to R 16 and was tested on a real-world mobile manipulation task. A video showcasing our experimental results is available at A video showcasing our experimental results is available at https://***/URjXbc_BiYg .

关键词： Genetic algorithm Reinforced genetic programming Generative heuristics Optimal path planning

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A robot action planner for automatic parts assembly

A robot action planner for automatic parts assembly

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1988 IEEE International Workshop on Intelligent Robots and Systems: Toward the Next Generation Robot and System, IROS 1988

作者： Hoermann, K. Rembold, U. Institute for Real-Time Computer Control Systems and Robotics University of Karlsruhe P.O.Box 6980 Karlsruhe7500 Germany

This paper describes a hierarchical robot action planning system for automatic assembly. Input to the system is a geometrical model of the parts to be assembled. The system provides a graphical editor to model the geometrical goal relationships between these parts. In the first step the ordering constraints between the different assembly operations are planned using a simulated disassembly of the final product. This results in a set of precedence graphs, which is used by the Action Sequence Planning Module to generate a gross plan to perform the overall assembly. In the next step this plan is refined by the Motion Planner. This involves Manipulator Path Planning, Fine Motion Planning and Grasp Planning. Output of the system is an executable robot action plan in an internal language. Using a Code Generation Module, different robot programming languages may be generated. © 1988 by the institute of Electrical and Electronics Engineers, Inc. (IEEE).

关键词： Assembly

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Machine Learning Strategies for Knowledge Acquisition in Autonomous Robot Systems

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IFAC Proceedings Volumes 1988年第16期21卷 5-15页

作者： R. Dillmann Institute for Real-Time Computer Control and Robotics University of Karlsruhe Karlsruhe FRG

Machine learning has been studied for more than 20 years. Most of the recent research contributions are basic and come from the areas of Cognitive Science and Artificial Intelligence. The classical domain of machine learning is related to vision and image analysis and image description. Since about five years there has been encreased activity to apply and to extend these general learning methods to really complex systems such as autonomous robots. The purpose of applied machine learning methods is to facilitate and to aid automatic construction and generation of knowledge based systems and to increase the system performance with time. Autonomous robot systems will operate in an unknown real environment and are based on the interaction of the basic system components such as action planner, plan executive and action monitor which need knowledge about the real world and knowledge about how to behave to reach a given goal. A robot system can learn if it is able to make changes and extensions in its behavioural control structure that enables it to better perform a given task. This includes acquisition of declarative procedural knowledge, the developement of manipulative and cognitive skills through instruction and practice as well as the organisation of knowledge into efficient representations. The purpose of automatic self-configurating or self-modifying representations is to make experience based knowledge available for possible future use in the context of increasing robot system performance. This paper reviews some general methods of machine learning application and some first results achieved to date.

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