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Doppler radars are low cost and light weight sensors that have a potential to find wide applications in building a large team of mobile vehicle platforms. Because of the nonlinearity associated with the measurement from Doppler radars, it is both interesting and challenging to extract meaningful information from the low cost sensors. Building upon the authors' previous work on self localization with...
In this paper, we report on a body state and ground profile estimator for a snake-like robot executing a rolling gait to travel from flat ground to a slope. With the help of the estimator, the snake-like robot can adaptively adjust the body shape and locomotion speed by changing the gait parameters for the purpose of tackling a steep slope. Specifically, we propose a repeating sequence of continuous...
Situation information and sensor information are differentiated and a method for computing the situation information expected value (SIEV) is presented for use in Information Based Sensor Management (IBSM). Nine case pairs are evaluated in which the sensor capabilities vary among poor, average, and good sensors, and the goal lattice values vary among attack, defend, and stealth modes showing that...
With the ubiquity of information distributed in networks, performing recursive Bayesian estimation using distributed calculations is becoming more and more important. There are a wide variety of algorithms catering to different applications and requiring different degrees of knowledge about the other nodes involved. One recently developed algorithm is the distributed Kalman filter (DKF), which assumes...
This paper proposes an efficient implementation of the multi-sensor generalized labeled multi-Bernoulli (GLMB) filter. The solution exploits the GLMB joint prediction and update together with a new technique for truncating the GLMB filtering density based on Gibbs sampling. The resulting algorithm has a complexity in the order of the product of the number of measurements from each sensor, and quadratic...
Decentralized data fusion is a challenging task. Either it is too difficult to maintain and track the information required to perform fusion optimally, or too much information is discarded to obtain informative fusion results. A well-known solution is Covariance Intersection, which may provide too conservative fusion results. A less conservative alternative is discussed in this paper, and generalizations...
A coal mine rescue snake robot with four orthogonal joints is developed. Taking the robot as an experimental platform, aiming at how to model and identify the environment of the coal mine tunnel after the disaster, a multi sensor data fusion algorithm based on genetic algorithm optimization of the variable structure fuzzy neural network (GAFNN) is proposed. Firstly, the fuzzy neural network model...
In this paper, we consider the problem of scheduling an agile sensor to perform an optimal control action in the case of the multi-target tracking scenario. Our purpose is to present a random finite set (RFS) approach to the multi-target sensor management problem formulated in the Partially Observed Markov Decision Process (POMDP) framework. The reward function associated with each sensor control...
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