基于气垫式越野机器人参数识别算法及其采样点选取规则的必要性和可行性

The Necessity and Feasibility based on the Parameter Identification Algorithm of Air Cushion Cross-Country Robot Rule Selection and Sampling Point

对土壤参数的识别是软地面越野机器人运行性能进行优化的关键要素,而且在实施的过程中还要对准确性问题以及多解问题进行处理。根据气垫式越野机器人的垂向力控制自由度,通过g算法可以对土壤推力的个别的参数进行识别,这样就解决了软地面越野机器人运行的各种问题。另外,要实现g算法就需要有三个采样点,还要对测量噪声以及状态噪声导致的土壤参数估值误差进行限制,所以设立采样点的选取规则非常必要。本文通过对不同测量噪声以及状态噪声水平下的估值准确性试验结果的介绍,论述了气垫式越野机器人参数识别算法及其采样点选取规则的必要性和可行性。

The identification of soil parameters is the key factor to performance of soft ground cross-country robot were optimized,and during the process of implementing but also on the accuracy of processing and multi solution problem. According to the aircushion type cross-country robot vertical force control degrees of freedom, through the G algorithm can separate parameters on soilthrust were identified, which solves various problems of soft ground cross-country robot operation. In addition, in order to realizethe G algorithm requires three sampling points, limit of soil parameter estimation error to the measurement noise and the noisecaused by the establishment of the state, so the selection rules of sampling points is very necessary. Based on the different measure-ment noise and noise level estimation accuracy of test results is introduced, the necessity and feasibility of the parameter identifica-tion algorithm for air cushion cross-country robot and its sampling point selection rule.