Actuated car doors with more than one degree of freedom are a desirable means to boost the convenience of the access to cars. This paper outlines the problems connected with providing an intuitive, comfortable and saf...
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Actuated car doors with more than one degree of freedom are a desirable means to boost the convenience of the access to cars. This paper outlines the problems connected with providing an intuitive, comfortable and safe operation of such doors. An advanced control system is proposed that overcomes these problems. First, a vision system for the monitoring of the workspace of the door is described. The data gathered is utilized by a collision avoidance method, which enables a safe operation of the car door. Second, a method for the support of the manual handling of the door is provided, which is based on predefined convenient paths for the specific kinematics of the door. Finally, the proposed control system is applied to a virtual car door, with successful results.
A classification system for vehicle rear detection in images is presented. The classification system consists of an expert system for preselecting relevant regions in an image and a subsequent machine learning classif...
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A classification system for vehicle rear detection in images is presented. The classification system consists of an expert system for preselecting relevant regions in an image and a subsequent machine learning classifier. Both utilize specifically designed features for the application. The latter classifier is implemented by a generalized radial basis function (GRBF) algorithm to assure the interpretability of the detection system. The GRBF is constructed based on the kernel of an ensemble method classifier, the random forest (RF) algorithm in order to achieve a low generalization error. The high accuracy of the proposed technique for vehicle rear detection is validated using data from real traffic situations.
This paper describes the motivation and learning subsystems of Arisco which is a mechatronic head with interactive capacity which includes high expressivity through gesturing, voice recognition, text to speech generat...
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ISBN:
(纸本)9781424420575
This paper describes the motivation and learning subsystems of Arisco which is a mechatronic head with interactive capacity which includes high expressivity through gesturing, voice recognition, text to speech generation, visual tracking, and internet information retrieval. The general architecture is first described in the paper. Then, the learning capacity of Arisco is addressed. It learns and performs associations between different stimulus responses through several dynamic neural networks, guided by motivational drives. A number of experiments are discussed, covering stimulus competition, habituation, classical and operant conditioning.
The video shows a rich multi-modal multi-user telepresence system, which was developed within the SFB453 funded by the German Research Foundation (***). As a complex application scenario, the remote repairing of a bro...
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The video shows a rich multi-modal multi-user telepresence system, which was developed within the SFB453 funded by the German Research Foundation (***). As a complex application scenario, the remote repairing of a broken pipe is presented in this paper. The system basically consists of two operator-teleoperator- pairs. While one of the operators interacts with a stationary human- system-interface, the other operator uses a mobile one. Both systems provide visual, auditory, and haptic feedback and enable to control the motion of head, arms, and grippers as well as the locomotion of the corresponding teleoperator.
This paper presents the design of the cognitive automobile in Munich. The focus of the capabilities shown here is the navigation on highways and rural roads. The emphasis on higher speed requires early detection of fa...
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This paper presents the design of the cognitive automobile in Munich. The focus of the capabilities shown here is the navigation on highways and rural roads. The emphasis on higher speed requires early detection of far field objects, so a multi focal active vision with gaze control is essential. For increased robustness lidar range sensors are combined with vision using an object fusion approach. An elaborate safety concept and a verification stage ensure a safe behavior of the vehicle in all situations. A communication system enables the vehicle to perform cooperative perception and action together with similar intelligent vehicles.
In this paper an approach for control of autonomously flying robots with vertical take off and landing capabilities (VTOL) is presented. After reviewing that the motion description for different VTOL-robots is very si...
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In this paper an approach for control of autonomously flying robots with vertical take off and landing capabilities (VTOL) is presented. After reviewing that the motion description for different VTOL-robots is very similar, the general control scheme for VTOL-robots is presented. This scheme is based on linearisation and decoupling using inversion of the system model blocks. To compensate the model uncertainties and disturbances two additional parts are included into the controller: a reduced state observer based on a robot motion model as well as a disturbances observer and compensator for orientation control. The presented approach was applied to two different VTOL-robots: a helicopter and a quad-rotor. In real flight experiments it was verified that the presented general but simple controller provides sufficient performance for a wide range of practical applications.
Cognitive automobiles consist of a set of algorithms that cover a wide range of processing levels: from low-level image acquisition and feature extraction up to situation assessment and decision making. The modules im...
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Cognitive automobiles consist of a set of algorithms that cover a wide range of processing levels: from low-level image acquisition and feature extraction up to situation assessment and decision making. The modules implementing them are naturally characterized by decreasing data rates at higher levels, because raw data is discarded after evaluation, and increasing processing intervals, as knowledge based levels require longer computation times. The architecture presented in this papers offers a method to interchange information with different temporal resolutions liberally among modules with distinct cycle times and real-time demands. It allows effortless buffering of raw data for subsequent data fusion and verification, facilitating innovative processing structures. The paper is completed by measurements demonstrating the achieved real-time capabilities on our selected hardware architecture.
A wind farm typically consists of a large number of individual wind turbine generators (WTGs) connected by an internal electrical network. To study the impact of wind farms on the dynamics of the power system, an impo...
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We present results of a collaboration project, during which parts of General Motors' north American vehicle supply chain have been modeled and evaluated. A variant of colored stochastic Petri nets has been develop...
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We present results of a collaboration project, during which parts of General Motors' north American vehicle supply chain have been modeled and evaluated. A variant of colored stochastic Petri nets has been developed for this task, and support for model creation and performance evaluation was implemented in our tool timeNET. Variations of the model and their stepwise evaluation lead to suggestions about how the supply chain can be reorganized in order to improve the time between customer order and vehicle delivery (order-to-delivery time).
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