This paper addresses the problem of statistical model selection for model-based multisensor fusion problems. The minimal representation size (MRS) criterion is used as a basis for the selection of a minimal complexity...
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This paper addresses the problem of statistical model selection for model-based multisensor fusion problems. The minimal representation size (MRS) criterion is used as a basis for the selection of a minimal complexity model among a class of stored models, and in addition enables the selection of parameterization, scaling, and data sub-sampling. This use of an information-based criterion results in a `universal yardstick' for model selection which is easily adapted to new combinations of sensors and parameters. Each sensor is characterized by a constraint equation defined in the measurement space of observed sensor data. The search for the best model structure is conducted using a polynomial time hypothesize and test algorithm that uses constraining data feature sets (CDFS) to instantiate environment models. Analytical formulation of the minimal representation size model selection for tactile-visual fusion with an anthropomorphic robot hand is presented.
A robust neural network (NN) output feedback scheme is proposed for the motion control of rigid robots. A dynamic NN observer is presented to estimate the joint speeds. The stability of a closed-loop system composed o...
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A robust neural network (NN) output feedback scheme is proposed for the motion control of rigid robots. A dynamic NN observer is presented to estimate the joint speeds. The stability of a closed-loop system composed of a robot, a NN observer, and a NN controller is proven. The NN weights in both the observer and the controller are tuned online, with no off-line learning phase required. Most importantly, we can guarantee the boundness of the estimated velocities, the position tracking errors, and the NN weights. Also no exact knowledge of the robot dynamics is required so that the NN controller is model-free and so applicable to any type of rigid robot. When compared with adaptive-type controllers, we do not require persistent excitation conditions, linearity in the unknown system parameters, or the tedious computation of a regression matrix. Thus the new NN approach represents an improvement over adaptive techniques.
For the problem of nonholonomic motion planning in the presence of obstacles, a path-iteration algorithm with an "exterior penalty" function has recently been proposed. The convergence of the iterative algor...
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For the problem of nonholonomic motion planning in the presence of obstacles, a path-iteration algorithm with an "exterior penalty" function has recently been proposed. The convergence of the iterative algorithm requires the avoidance of singular controls. With the inclusion of a penalty function, the set of singular control may increase substantially. In this paper, we propose a specific guideline for choosing the penalty function which does not introduce additional singular controls. In the case of the N-trailer system, this result can be used to guarantee the convergence of the path planning algorithm. To demonstrate the effectiveness of the proposed algorithm, simulation results are included.
A class of Iterative algorithms have been proposed in recent years for the nonholonomic motion planning problem. The convergence of these algorithms predicates on the control signal in each iteration be "nonsingu...
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A class of Iterative algorithms have been proposed in recent years for the nonholonomic motion planning problem. The convergence of these algorithms predicates on the control signal in each iteration be "nonsingular". At the present, the singularity structure is only identified for the unicycle and front-wheel-drive car kinematic models. In this paper, we extend the consideration to all systems reducible to one-chain form, which include unicycle, car, as well as any N-trailer system. In particular, we show that a control is singular if and only if the first control variable is identically zero. We also identified all singular controls for the ball rolling on a plate problem. which is not reducible to the one-chain form.
TETROBOT is a modular system for the design, implementation, and control of a class of highly redundant parallel robotic mechanisms. This paper describes new experimental results based on evaluation of prototype confi...
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TETROBOT is a modular system for the design, implementation, and control of a class of highly redundant parallel robotic mechanisms. This paper describes new experimental results based on evaluation of prototype configurations with up to 18 nodes, 48 links and 15 actuators. TETROBOT is an actuated robotic structure which may be reassembled into many different configurations while still being controlled by the same hardware and software architecture. Implementations of a double octahedral platform, a tetrahedral arm and a six-legged walker, constructed from the same set of parts, are described. The TETROBOT system addresses the needs of application domains, such as space, undersea, mining, and construction, where adaptation to unstructured and changing environments and custom design for rapid implementation are required.
Parallel robots can be built by linking together unit cells in configurations which retain the static determinacy of the overall structure. In the Tetrobot system, the kinematics of these concatenated structures can b...
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Parallel robots can be built by linking together unit cells in configurations which retain the static determinacy of the overall structure. In the Tetrobot system, the kinematics of these concatenated structures can be solved by propagation of solutions through connected graphs of linked modules. In this paper, we examine the synthesis of unit cells which could be used in creating these structures and retain the ability to compute the kinematics for control of the actuated system. Admissible unit cells are shown to form families in two- and three-dimensions, and a set of synthesis rules is described which generates the members of these families recursively for each generations. The resulting set of modules comprises a broad set of useful cells which can be used to design parallel robots and guarantee the computability of their kinematics on a cell-by-cell basis.
This paper presents an application of feature-based visual servoing to achieve accurate and robust 3D filament alignment. Two orthogonal cameras are used to localize the five degrees of freedom of an axi-symmetric fil...
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This paper presents an application of feature-based visual servoing to achieve accurate and robust 3D filament alignment. Two orthogonal cameras are used to localize the five degrees of freedom of an axi-symmetric filament. An algorithm for precisely estimating the center and orientation features of a filament in a camera view is described. The use of feature-based servoing overcomes the difficulty of 3D camera calibration in a factory environment. These features drive a PID control loop for each view. The two views are coupled in one degree of freedom, and the multiple-view controller switches between two single-view controllers to achieve 3D servoing. The overall accuracy achieved is in thousandths of an inch. Experimental results on the performance of the control algorithm are discussed. Models explaining the system behavior are presented. The use of visual servoing in this application far exceeds the positioning accuracy and the repeatability of human operators.
This paper introduces a new feedback algorithm for steering a point robot through an obstacle field. The key innovation is the use of a circulatory field to rotate the robot path around the obstacles instead of the co...
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This paper introduces a new feedback algorithm for steering a point robot through an obstacle field. The key innovation is the use of a circulatory field to rotate the robot path around the obstacles instead of the common potential field which repels the robot. This idea is motivated by a charged particle in a magnetic field generated by a current flowing around the obstacle. In constrast, the potential field approach is associated with a repulsive static electric field generated by charges of the same polarity as the robot, on the obstacle. The circulatory field does not generate any spurious local minimum as it does not change the total energy of the system. By combining with an attractive potential field associated with the desired destination, this method achieves global convergence while avoiding collisions with obstacles.
An object-oriented modular approach to the engineering of complex robotic systems emphasizes reliability, reusability, ease of development, and user and network interfaces. This modular approach integrates many archit...
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An object-oriented modular approach to the engineering of complex robotic systems emphasizes reliability, reusability, ease of development, and user and network interfaces. This modular approach integrates many architectural principles and computational techniques which support adaptive and learning capability at the local, modular level. The TETROBOT is a modular and reconfigurable robotic system which was developed to demonstrate the reliable performance in a wide variety of task domains through reconfiguration of the same fundamental hardware and software components. Such a modular approach emphasizes the synthesis and integration of engineering modules and takes advantage of object-oriented engineering principles to design for a family of tasks. This paper provides an overview of the TETROBOT modular system and describes three modular systems in other applications domains.
A compliance-governed (redundant) manipulator is the main subject of the article, and its global quasi-static behaviors are studied. To implement those behaviors in an actual manipulator, mathematical compliance parad...
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