In vision-based robotic arc welding had some degree of autonomy functions, sensors must be used to detect the position and orientation of a weld seam and determine its path in order to carry out the autonomy of weldin...
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ISBN:
(纸本)9783540733737
In vision-based robotic arc welding had some degree of autonomy functions, sensors must be used to detect the position and orientation of a weld seam and determine its path in order to carry out the autonomy of welding process. This paper represented a method to recognize whole seam in complex robotic welding environment. According to the parameter we defined to judge the degree of image noise, then different size of filter windows were selected to preprocess the image. Algorithm to eliminate effect of complex changing background is proposed. Parameters are defined to judge if it is necessary to use this algorithm. The threshold and edge detect algorithms that adapt to the recognition for robotic welding environment is also addressed in this paper. The experiments give the recognition results of two different shapes and material of seams. The results showed that the recognized method was robust to the recognition of macroscopic seam for complex robotic welding environment.
Electronic devices do the impossible in that they introduce new measures and monitors, achieve the automation of manual tasks, and potentially enable the relocation of care and patient monitoring to less intensive set...
Electronic devices do the impossible in that they introduce new measures and monitors, achieve the automation of manual tasks, and potentially enable the relocation of care and patient monitoring to less intensive settings. But at the same time they circumvent established processes of external peer review and calibration, professional responsibility, and consumer understanding. Most innovations seek to reduce risk, but any innovation introduces new Risk. Health has proven systems to assess Risk, but devices circumvent these. Examples will be given of various risks, and the argument put for greater investment in shared knowledge development. More investment in reporting and evaluation are needed, based on an philosophy of Social Responsibility in Science.
The Orthoglide is a Delta-type PKM dedicated to 3-axis rapid machining applications that was originally developed at IRCCyN in 2000-2001 to meet the advantages of both serial 3-axis machines (regular workspace and hom...
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The Orthoglide is a Delta-type PKM dedicated to 3-axis rapid machining applications that was originally developed at IRCCyN in 2000-2001 to meet the advantages of both serial 3-axis machines (regular workspace and homogeneous performances) and parallel kinematic architectures (good dynamic performances and stiffness). This machine has three fixed parallel linear joints that are mounted orthogonally. The geometric parameters of the Orthoglide were defined as function of the size of a prescribed cubic Cartesian workspace that is free of singularities and internal collision. The interesting features of the Orthoglide are a regular Cartesian workspace shape, uniform performances in all directions and good compactness. In this paper, a new method is proposed to analyze the stiffness of overconstrained Delta-type manipulators, such as the Orthoglide. The Orthoglide is then benchmarked according to geometric, kinematic and stiffness criteria: workspace to footprint ratio, velocity and force transmission factors, sensitivity to geometric errors, torsional stiffness and translational stiffness.
Due to the advent of pervasive and distributed computing, the shift in data processing paradigms is quite visible in many applications (e.g., communication, industrial control, public administrations, geographically d...
Due to the advent of pervasive and distributed computing, the shift in data processing paradigms is quite visible in many applications (e.g., communication, industrial control, public administrations, geographically distributed business, etc.). The switch from centralized processing paradigm to the local processing paradigm is becoming a necessity due to many factors such as: security, privacy, limitation of the transmission bandwidth, time processing, business strategies and rules, limited power supply, etc. In this paper, a clustering approach dedicated to distributed data emanating from diverse sources is proposed and evaluated. This approach is guided by two principles: coordination and collaboration among various data sources to cope with the problem of privacy and corporate confidentiality in an appropriate way.
S-learning is a sequence-based learning algorithm patterned on human motor behavior. Discrete-time and quantized sensory information is amassed in real-time to form a dynamic model of the system being controlled and i...
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S-learning is a sequence-based learning algorithm patterned on human motor behavior. Discrete-time and quantized sensory information is amassed in real-time to form a dynamic model of the system being controlled and its environment. No explicit model is provided a priori, nor any hint about what the structure of the model might be. As the core of a Brain-Emulating Cognition and control Architecture (BECCA), S-Learning provides a mechanism for human-inspired learning, memory, and control in machines. In a simulation of a point-to-point reaching task, S-Learning demonstrates several attributes of human motor behavior, including learning through exploration and task transfer.
In this paper we propose a novel architecture for the control plane of an application aware optical burst switching (OBS) network, able to support grid computing applications. We suggest the use of the session initiat...
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In this paper we propose a novel architecture for the control plane of an application aware optical burst switching (OBS) network, able to support grid computing applications. We suggest the use of the session initiation protocol (SIP) to implement a protocol layer between the grid specific control messages and the network control plane. The proposed architecture was implemented in an existing OBS network test-bed and was successfully tested as described in the paper.
In this paper we consider autonomous control of a real snake-like robot using reinforcement learning. We focus on curse of dimensionality and lack of generality, and point out that the causes of the problems are not i...
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In this paper we consider autonomous control of a real snake-like robot using reinforcement learning. We focus on curse of dimensionality and lack of generality, and point out that the causes of the problems are not in learning algorithm but in neglect of properties of the real world. To solve the problems we propose new framework in which body of robot abstract general meaning by using properties of the real world as information processor. We apply the proposed framework for controlling a snake-like robot and confirm that the two problems are solved simultaneously, without changing learning algorithm at all. To demonstrate the effectiveness of the proposed framework experiments has been carried out.
Multiple-input multiple-output (MIMO) wireless antenna systems are known as the effective means to achieve high capacity over wireless links. In this paper, we propose an adaptive packet-by-packet scheduling scheme, w...
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Multiple-input multiple-output (MIMO) wireless antenna systems are known as the effective means to achieve high capacity over wireless links. In this paper, we propose an adaptive packet-by-packet scheduling scheme, which considers channel state information, user's average throughput, and queueing state information when making scheduling decision. Our proposed scheduler, adaptive proportional fairness with queue length consideration (APF-Q), is work conserving and can provide low delay of users in a fair way. Numerical results taking into consideration traffic characteristics and the mobility of users demonstrate the superior performance of the proposed APF-Q scheduler.
Space tethered autonomous robotic satellite (STARS) is being developed for technical verification of tethered space robot (TSR), which is a new type of space robot system proposed in the previous work. The STARS consi...
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Space tethered autonomous robotic satellite (STARS) is being developed for technical verification of tethered space robot (TSR), which is a new type of space robot system proposed in the previous work. The STARS consists of mother and daughter satellites connected by tether. The mother satellite deploys tether having the daughter satellite at its end. The daughter satellite is TSR, and has one arm link, whose end is attached to tether. Then, attitude control by arm link motion is possible under condition that tether tension is applied. Main mission of the STARS follows sequence as: the mother satellite release the daughter satellite; attitude of the daughter satellite is controlled by arm link motion; the camera mounted on the daughter satellite takes a picture during deployment; the daughter satellite docks with the mother satellite. The system of the STARS consists of power, data handling, communication, camera, attitude control, structure, deployment, and robotic subsystems. Deployment and robotic subsystems are specific compared to other pico-satellite. Main objective of the deployment subsystem is to deploy and to retrieve tether. On the other hand, main objective of the robotic subsystem is to control attitude of the daughter satellite.
An elegant solution to the problem of instrumenting paralyzed limbs with artificial sensors for use with closed-loop FES systems is to use natural sensors, such as muscle afferent activity as feedback for the artifici...
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An elegant solution to the problem of instrumenting paralyzed limbs with artificial sensors for use with closed-loop FES systems is to use natural sensors, such as muscle afferent activity as feedback for the artificial controller. Longitudinal intra-fascicular electrodes (LIFEs) are electrodes that have shown promise in this application. As a peripheral nerve interface, they are designed to be placed inside the peripheral nerve, but near potentially active muscles and the stimulating electrode. Artefacts from EMG and stimulation remain limiting factors in signal acquisition. Here, we present a technique for improving the signal-to-noise ratio which consists of wrapping a shield around the implant site of the recording electrode. Preliminary results obtained during in-vivo experiments suggest that the shielding increases the level of the neural signal in the recordings.
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