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Dexterity analysis and intelligent trajectory planning of redundant dual arms for an upper body humanoid robot
Industrial Robot ( IF 1.8 ) Pub Date : 2021-07-31 , DOI: 10.1108/ir-12-2020-0279
Shifa Sulaiman 1 , A.P. Sudheer 1
Affiliation  

Purpose

Most of the redundant dual-arm robots are singular free, dexterous and collision free compared to other robotic arms. This paper aims to analyse the workspace of redundant arms to study the manipulability. Furthermore, multi-layer perceptron (MLP) algorithm is used to determine the various joint parameters of both the upper body redundant arms. Trajectory planning of robotic arms is carried out with the help of inverse solutions obtained from the MLP algorithm.

Design/methodology/approach

In this paper, the kinematic equations are derived from screw theory approach and inverse kinematic solutions are determined using MLP algorithm. Levenberg–Marquardt (LM) and Bayesian regulation (BR) techniques are used as the backpropagation algorithms. The results from two backpropagation techniques are compared for determining the prediction accuracy. The inverse solutions obtained from the MLP algorithm are then used to optimize the cubic spline trajectories planned for avoiding collision between arms with the help of convex optimization technique. The dexterity of the redundant arms is analysed with the help of Cartesian workspace of arms.

Findings

Dexterity of redundant arms is analysed by studying the voids and singular spaces present inside the workspace of arms. MLP algorithms determine unique solutions with less computational effort using BR backpropagation. The inverse solutions obtained from MLP algorithm effectively optimize the cubic spline trajectory for the redundant dual arms using convex optimization technique.

Originality/value

Most of the MLP algorithms used for determining the inverse solutions are used with LM backpropagation technique. In this paper, BR technique is used as the backpropagation technique. BR technique converges fast with less computational time than LM method. The inverse solutions of arm joints for traversing optimized cubic spline trajectory using convex optimization technique are computed from the MLP algorithm.



中文翻译:

上身仿人机器人冗余双臂灵巧度分析与智能轨迹规划

目的

与其他机械臂相比,大多数冗余双臂机器人具有奇异自由、灵巧和无碰撞的特点。本文旨在分析冗余臂的工作空间以研究可操纵性。此外,多层感知器(MLP)算法用于确定两个上身冗余臂的各种关节参数。机械臂的轨迹规划是在从 MLP 算法获得的逆解的帮助下进行的。

设计/方法/方法

在本文中,运动学方程是从螺旋理论方法推导出来的,并使用 MLP 算法确定逆运动学解。Levenberg-Marquardt (LM) 和贝叶斯调节 (BR) 技术被用作反向传播算法。比较两种反向传播技术的结果以确定预测精度。然后使用从 MLP 算法获得的逆解来优化三次样条轨迹,以借助凸优化技术避免臂之间的碰撞。借助臂的笛卡尔工作空间分析冗余臂的灵巧性。

发现

通过研究手臂工作空间内存在的空隙和奇异空间来分析冗余手臂的灵巧性。MLP 算法使用 BR 反向传播以较少的计算工作确定唯一的解决方案。MLP算法得到的逆解利用凸优化技术有效地优化了冗余双臂的三次样条轨迹。

原创性/价值

大多数用于确定逆解的 MLP 算法都与 LM 反向传播技术一起使用。在本文中,BR技术被用作反向传播技术。BR 技术收敛速度快,计算时间比 LM 方法少。使用凸优化技术遍历优化三次样条轨迹的臂关节的逆解是从 MLP 算法计算出来的。

更新日期:2021-07-31
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