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Optimal robot trajectory planning using dynamic models.

机译:使用动态模型的最佳机器人轨迹规划。

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This dissertation presents algorithms for the solution of the robot trajectory planning problem. The strategies presented consider two planning approaches: The first is a simple approach with a simple dynamical model that avoids the complicated dynamics of an arm; the second is more sophisticated due to the consideration of the full dynamic equations of the manipulator.; The first algorithm developed falls in the first class. No consideration is given to the full dynamics. Instead two time intervals are considered: TA defined as time needed to accelerate from zero to maximum velocity and TJ defined as the time needed to achieve the transition from zero to maximum acceleration. This simple algorithm is developed at the joint level considering bounds on velocity, acceleration and jerk. The simplicity of the scheme makes it an efficient minimum time on-line trajectory generator.; The other algorithms developed correspond to the second class; the trajectories generated are governed by considering the complete dynamics. One algorithm considers the problem of optimizing energy while moving the arm's tip along a predefined path in Cartesian coordinates. Using time scaling techniques, the dynamic equations are mapped into the path distance thus reducing the problem into a one degree of freedom motion along the path. The problem is posed as a classical minimum fuel problem. Dynamic Programming is used to achieve the optimal torques which end up to follow the mixed unordered sequences of the control's Bang-Off-Bang policies.; Another algorithm considers the problem of finding the optimal cubic Bezier path in configuration space such that the time needed for the transition is minimum. Again the complete dynamics are considered and a search strategy is proposed to find the optimal Bezier cubic path. In this algorithm time scaling is also used to simplify the dimensionality and the concept of optimizing in joint space is introduced.; Simulations and examples are presented for the algorithms, whenever possible comparisons are made with related works. Finally some key ideas for future work are presented.
机译:本文提出了解决机器人轨迹规划问题的算法。提出的策略考虑了两种规划方法:第一种是具有简单动力学模型的简单方法,可以避免复杂的手臂动力学;第二种是由于考虑了机械手的完整动力学方程而更加复杂。开发的第一个算法属于第一类。没有考虑全部动态。取而代之的是考虑两个时间间隔:TA定义为从零加速到最大速度所需的时间,TJ定义为实现从零加速到最大加速度所需的时间。这个简单的算法是在联合级别上开发的,考虑了速度,加速度和加速度的限制。该方案的简单性使其成为有效的最小时间在线轨迹发生器。开发的其他算法对应于第二类。通过考虑完整的动力学来控制产生的轨迹。一种算法考虑了在沿笛卡尔坐标中的预定路径移动手臂的尖端时优化能量的问题。使用时间缩放技术,将动态方程式映射到路径距离中,从而将问题简化为沿路径的一个自由度运动。该问题被称为经典的最小燃油问题。动态编程用于获得最佳转矩,该转矩最终遵循控件的Bang-Off-Bang策略的混合无序序列。另一算法考虑了在配置空间中找到最佳三次贝塞尔曲线路径的问题,从而使过渡所需的时间最小。再次考虑了完整的动力学,并提出了寻找最佳贝塞尔三次方路径的搜索策略。在该算法中,还使用时间缩放来简化维数,并介绍了在关节空间中进行优化的概念。只要与相关工作进行了可能的比较,就会为算法提供仿真和示例。最后,提出了一些未来工作的关键思想。

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