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Secret reconnaissance and surveillance in spatially constrained spot are demanded in many antiterrorism activities. The special applications require a kind of miniature mobile robot to function covertly in highly confined environments. Thrown deployment mode for robots could be adopted. However, the crucial problem coping with the impact resulted from thrown miniature mobile robots' falling to the...
Walking pattern generation has been a crucial issue for humanoid robot. To generate more natural walking patterns, and determine parameters more reasonably, this paper presents a method for humanoid walking pattern generation based on human walking characteristics. The characteristics of human walking parameters were obtained by capturing and analyzing human walking data. Walking pattern parameters...
Large-scope surveillance is demanded in many civilian activities. These special tasks require a kind of autonomous mobile robot. We present a miniature autonomous robot ("BMS-1", BIT MicroScout-1) for large-scale indoor reconnaissance and surveillance missions. However, the small volume of BMS-1 results in the difficulty of implementing autonomous capacity due to limited computational and...
By redefining multiplier associated with inequality constraint as a positive definite function of the originally-defined multiplier, u2j ,i = 1,2, ----, m, say, the nonnegative constraints imposed on inequality constraints in Karush-Kuhn-Tucker necessary conditions are removed completely. Hence it is no longer necessary to convert inequality constraints into equality constraints by slack variables...
Secret surveillance in tightly constrained spaces is demanded in many military and civilian activities, such as cave-in enemy raids and indoor hostage rescue missions. These special applications require a kind of miniature mobile robot to function covertly in highly confined environments. However, the crucial problem resulted from the small volume of miniature robots is the difficulty of packing locomotion,...
In this paper, a new hybrid learning strategy composed of K-means clustering algorithm and Kalman filtering is employed to train radial based function (RBF) neural network for fault diagnosis in satellite attitude determination system. Because Kalman filtering and K-means clustering algorithm both adopt linear update rule, their combination produces a new hybrid training algorithm that can converge...
By redefining multiplier associated with inequality constraint as a positive definite function of the originally-defined multiplier, ui2, i = 1, 2,..., m, say, the nonnegative constraints imposed on inequality constraints in Karush-Kuhn-Tucker necessary conditions are removed completely. Hence it is no longer necessary to convert inequality constraints into equality constraints by slack variables...
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