摘要
目前仿生机器人的研究主要集中在轮式(履带)机器人和爬行机器人上,与这两种机器人相比,腿式跳跃机器人能够跨越较大的障碍物,能够在比较复杂的地形环境中运动,而成为了近年来国内外仿生机器人领域研究的热点对象。
本文总结了单腿跳跃机器人的发展现状,提出了本课题的研究内容。
针对以往单腿跳跃机器人的设计局限性,提出一种新机构模型——仿袋鼠单腿跳跃机器人机构模型,并对其进行动力学建模和运动仿真,仿真结果验证了动力学模型的正确性,为机器人的运动控制和结构优化奠定了理论基础。
针对仿袋鼠单腿跳跃机器人支撑相是二阶非完整约束系统的这一特点,从非线性控制理论出发,以动力学模型为基础,推导出仿袋鼠单腿跳跃机器人在支撑相的平衡点线性化系统,并证明其在支撑相是线性可控的,为机器人的稳定控制提供了理论依据。
针对单腿跳跃机器人系统是一种非线性系统,而周期运动是非线性系统的一类重要解,探讨了搜索周期运动的方法及算法,并以一种简单的单腿跳跃机器人模型为例,采用所述方法及算法找到了其被动周期运动。
最后一部分针对现有的搜索周期运动方法的最大一个缺点:即其初始条件是手动修改,这种手动修改初始条件的方法具有盲目性,即经过无数次的尝试,才能找到所满意的初始条件,这样一来就非常费时,效率低下。因此,如果在确定初始条件前采用优化方法,找到合适的初始条件,那么就可以提高效率,避免了盲目性。
At present, bio-robots research mainly concentrated in the wheel (tracked) robots and crawling robots. Compared with these robots, legged hopping robots can leap relatively large obstacles and locomote on the more complex terrain, and they are the hotspot object of the bio-robots research fields in recent years.
In the paper, the research development of hopping robot is summarized, and the main issue of the paper is illustrated.
For the past one-legged hopping robots design limitations, a new mechanical model——kangaroo-like hopping robot with one leg is proposed, and its dynamics modeling and motion simulation were done, the results of the simulation verify the correctness of the dynamics model, which laid a theoretical basis for the robot motion control and structural optimization.
For the kangaroo-like hopping robot with one leg, the characteristics of its support phase is second-order nonholonomic constraint system, starting from the non-linear control theory, based on dynamics model, deduced the linear system of equilibrium point for the kangaroo-like hopping robot with one leg in the support phase, and proved that it is linearly controllability in the support phase, which provided a theoretical basis for the robot's stability control.
For a one-legged hopping robot system is a nonlinear system, and the periodic motion is an important solution of a class of nonlinear system, explored the searching methods and algorithms of the periodic motion, and a simple model of one-legged hopping robot for example, found its passive periodic motion by using the described methods and algorithms.
In the last part of the research, for the existing searching method of periodic motion, its biggest drawback is to manually modify the initial conditions, the manual modification of initial conditions had blindness, that is, after numerous attempts to find the satisfied initial conditions, so that it is very time-consuming and inefficient. Therefore, if prior to determin initial conditions we used an optimal way to find a suitable initial condition, it can improve efficiency, and avoid blindness.
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