为差速轮式机器人设计了考虑角速度约束的最优时间路径参数化方法。
TOPP-DWR: Time-Optimal Path Parameterization of Differential-Driven Wheeled Robots Considering Piecewise-Constant Angular Velocity Constraints
- 用分段常数角速度建模,统一处理多类运动约束。
- 通过松弛变量转化问题,实现高效求解且满足所有物理限制。
- 在真实场景中验证了算法实用性,适合高精度移动控制应用。
差速驱动轮式机器人(DWR)是移动机器人中最典型的一类,在机器人领域广泛应用。大多数高性能控制方法将轨迹的线速度和角速度作为控制参考,但现有时间最优路径参数化(TOPP)研究通常忽略角速度与关节速度约束,导致实际应用中控制性能下降。本文提出一种名为TOPP-DWR的系统性、实用型TOPP算法,适用于DWR及其他移动机器人。首先,采用非均匀B样条表示任务空间中的初始轨迹;其次,将分段常数角速度、关节速度、线速度及线加速度约束统一纳入TOPP问题,并以线速度约束形式统一表达。为提升数值计算效率,引入松弛变量,将问题转化为二阶锥规划(SOCP)。通过对比实验验证所提方法优势,定量指标显示TOPP-DWR可在满足全部约束条件下实现时间最优。最后,开展实地自主导航实验,验证了其在真实场景中的可行性。
原文摘要 · Abstract (English)
Differential-driven wheeled robots (DWR) represent the quintessential type of mobile robots and find extensive appli- cations across the robotic field. Most high-performance control approaches for DWR explicitly utilize the linear and angular velocities of the trajectory as control references. However, existing research on time-optimal path parameterization (TOPP) for mobile robots usually neglects the angular velocity and joint vel- ocity constraints, which can result in degraded control perfor- mance in practical applications. In this article, a systematic and practical TOPP algorithm named TOPP-DWR is proposed for DWR and other mobile robots. First, the non-uniform B-spline is adopted to represent the initial trajectory in the task space. Second, the piecewise-constant angular velocity, as well as joint velocity, linear velocity, and linear acceleration constraints, are incorporated into the TOPP problem. During the construction of the optimization problem, the aforementioned constraints are uniformly represented as linear velocity constraints. To boost the numerical computational efficiency, we introduce a slack variable to reformulate the problem into second-order-cone programming (SOCP). Subsequently, comparative experiments are conducted to validate the superiority of the proposed method. Quantitative performance indexes show that TOPP-DWR achieves TOPP while adhering to all constraints. Finally, field autonomous navigation experiments are carried out to validate the practicability of TOPP-DWR in real-world applications.
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