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Design and control of a micro ball-balancing robot (MBBR) with orthogonal midlatitude omniwheel placement

机译:具有正交中纬全方位轮放置的微球平衡机器人(MBBR)的设计和控制

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Ball-balancing robots (BBRs) are endowed with rich dynamics. When properly designed and stabilized via feedback to eliminate jitter, and intuitively coordinated with a well-designed smartphone interface, BBRs exhibit a uniquely fluid and organic motion. Unlike mobile inverted pendulums (MIPs, akin to unmanned Segways), BBRs stabilize both fore/aft and left/right motions with feedback, and bank when turning. Previous research on BBRs focused on vehicles from 50cm to 2m in height; the present work is the first to build significantly smaller BBRs, with heights under 25cm. We consider the unique issues arising when miniaturizing a BBR to such a scale, which are characterized by faster time scales and reduced weight (and, thus, reduced normal force and stiction between the omniwheels and the ball). Two key patent-pending aspects of our design are (a) moving the omniwheels to contact the ball down to around 20 to 30 deg N latitude, which increases the normal force between the omniwheels and the ball, and (b) orienting the omniwheels into mutually-orthogonal planes, which improves efficiency. Design iterations were facilitated by rapid prototyping and leveraged low-cost manufacturing principles and inexpensive components. Classical successive loop closure control strategies are implemented, which prove to be remarkably effective when the BBR isn't spinning quickly, and thus the left/right and fore/aft stabilization problems decompose into two decoupled MIP problems.
机译:平衡球机器人(BBR)具有丰富的动力。当通过反馈进行适当的设计和稳定以消除抖动,并与精心设计的智能手机界面进行直观协调时,BBR会表现出独特的流体运动和有机运动。与移动式倒立摆锤(MIP,类似于无人驾驶的Segway)不同,BBR具有稳定的前/后和左/右运动反馈,并在转弯时倾斜。先前对BBR的研究集中在高度从50cm到2m的车辆上;目前的工作是第一个建造高度小于25cm的BBR的方法。我们考虑将BBR缩小到这样的规模时会出现的独特问题,这些问题的特征是更快的时标和更轻的重量(因此,减小了飞轮和球之间的法向力和静摩擦力)。我们设计中的两个关键的正在申请专利的方面是(a)将万向轮移动到与球接触的位置,使其下降到大约20到30度N纬度,这会增加万向轮和球之间的法向力,以及(b)将万向轮定位到相互正交的平面,从而提高了效率。快速原型制作以及利用低成本制造原理和廉价组件促进了设计迭代。实施了经典的连续闭环控制策略,当BBR不能快速旋转时,这种策略被证明非常有效,因此左右稳定性和前/后稳定性问题分解为两个解耦的MIP问题。

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