首页> 外文会议>ASME International Design Engineering Technical Conferences;Computers and Information in Engineering Conference;Mechanisms and Robotics Conference >INDICES AND COMPUTATIONAL STRATEGY FOR UNMANNED GROUND WHEELED VEHICLE MOBILITY ESTIMATION AND ENHANCEMENT
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INDICES AND COMPUTATIONAL STRATEGY FOR UNMANNED GROUND WHEELED VEHICLE MOBILITY ESTIMATION AND ENHANCEMENT

机译:无人面地面车辆移动性估算和增强的指标和计算策略

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The United States Army began developing Unmanned Ground Vehicles (UGV) in the early 1900's. Concurrently, researchers developed and enhanced passenger and commercial ground vehicles. Although significant progress has been made for improving vehicle mobility for all ground vehicles throughout the past century, mobility has lacked a concise mutually agreed definition and analytical standardized criteria. The implementations of improved technologies, such as vehicle traction control, stability control, and torque vectoring systems require researchers to take a step back and reevaluate mobility criteria. UGVs require additional enhancement to include on-line mobility estimation since the vehicle cannot predict nor anticipate terrain conditions on their own prior to the vehicle traversing those conditions. This paper analyzes methodologies researchers have employed for defining and improving vehicle mobility of wheeled vehicles. The analysis is done from a view point of concurrent mobility methodologies' enhancement and applicability to wheeled UGVs. This analysis is then used to develop off-line and on-line analytical criterion for mobility estimation, and to derive a strategy which can be applied to wheeled vehicles, both manned and unmanned. The on-line mobility estimation enables the UGV to make control changes as the events occur rather than after the event, causing the vehicle to then optimize its reaction to regain control.
机译:美国陆军开始于1900年代初开发无人机(UGV)。同时,研究人员开发和增强了乘客和商业地面车辆。虽然在过去的世纪过去改善所有地面车辆的车辆移动性方面取得了重大进展,但流动性缺乏简洁的共同商定定义和分析标准化标准。改进技术的实现,例如车辆牵引力控制,稳定性控制和扭矩矢量系统需要研究人员避免退步并重新评估移动性标准。 UGVS需要额外的增强来包括在线移动性估计,因为车辆在车辆穿过那些条件之前不能在车辆之前预测或预测地形条件。本文分析方法研究人员采用了用于限定和改善轮式车辆的车辆移动性的研究人员。该分析是从同时移动方法的增强和适用性转向UGV的视角完成的。然后,该分析用于开发离线和在线分析标准进行移动性估计,并导出可以应用于轮式车辆的策略,既有载人和无人驾驶。在线移动性估计使UGV能够以事件发生而不是在事件之后进行控制,使得车辆能够优化其反应来重新获得控制。

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