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We propose a distributed algorithm for calibrating the intrinsic and extrinsic parameters of a Camera Sensor Network (CSN). We assume that only one of the cameras is calibrated and that the network graph, i.e. the graph over which the cameras communicate, is connected. Each camera uses simple algorithms based on epipolar geometry to obtain its calibration matrix as well as its pose relative to a reference...
We analyze the observability of the continuous and discrete states of discrete-time jump linear systems (JLSs) with deterministic inputs. We consider several definitions of observability for JLSs depending on whether some or all inputs are considered. Unfortunately, checking these definitions can involve an exponential number of rank tests on the parameters of the JLS when the discrete state sequence...
We propose a method based on sparse representation (SR) to cluster data drawn from multiple low-dimensional linear or affine subspaces embedded in a high-dimensional space. Our method is based on the fact that each point in a union of subspaces has a SR with respect to a dictionary formed by all other data points. In general, finding such a SR is NP hard. Our key contribution is to show that, under...
In this paper, a new approach for path generation and control of multi-agent systems is proposed. This method is based on global optimization techniques used for solving the inverse kinematic problem of redundant manipulators. Convergence of any performance function such as obstacle avoidance, collision avoidance, and heading angle to its global optimum is guaranteed by introducing a control law which...
In this paper, decentralized control algorithms for cooperative multi-agent manipulation systems are developed. To control the positions of the agents and the exerted forces on the object in the presence of uncertainties in the dynamics of the agents, two different methods are considered. In the first approach, robust control of the system is proposed. Using the Lyapunov stability method, the convergence...
In this paper, a new approach for online reactive path generation and control of multi-agent systems is proposed. This method is based on local optimization techniques used for solving the inverse kinematic problem of redundant manipulators. Convergence of the agents' velocities to the desired values in the null-space of the primary task is guaranteed by introducing a new control law. The efficacy...
In this paper, a neural network decentralized control for trajectory tracking of robot manipulators is developed. The proposed decentralized control allows the overall closed-loop system to be stabilized while making the tracking error to be uniformly ultimately bounded (UUB), without having any prior knowledge of the robot manipulator dynamics. The interconnections in the dynamic equations of each...
In this paper an adaptive fuzzy decentralized control algorithm for trajectory tracking of robot manipulators is developed. The proposed decentralized control algorithm allows the overall closed-loop system to be stabilized while making the tracking error to be uniformly ultimately bounded (UUB), without having any prior knowledge of the robot manipulator dynamics. The interconnections in the dynamic...
In this paper a decentralized control scheme for multiple cooperative manipulators is developed to achieve the desired performance in motion and force tracking, in the presence of uncertainties in dynamic equations of the robots. To eliminate the effects of uncertainties in the closed-loop performance, a new adaptive control algorithm is proposed. Based on the Lyapunov stability method, it is proved...
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