Abstract

In this paper, a grasping posture control for a robotic arm is developed based on novel adaptive particle swarm optimization (PSO) for the home service robot. To grasp an object using the robotic arm of the home-service robot, both the spatial coordinates of the target and the appropriate collocation of the grasping posture should be examined. In this paper, we present another method for dealing with this problem, which integrates the artificial bee colony (ABC) algorithm into the adaptive particle swarm optimization (APSO) algorithm, where the mutation concept of the scout bee in the ABC algorithm is used to increase the diversity of the particles. In addition, adaptive acceleration coefficients and adaptive inertia weight are presented to ameliorate the convergence rate of the PSO algorithm. We name this control scheme AIWCPSO-S, which represents Adaptive Inertia Weight and acceleration Coefficients PSO with the aid of the Scout bee. Performance comparisons of existing ABC, global ABC, adaptive inertia weight PSO, low-discrepancy sequence initialized PSO algorithm with high-order nonlinear time-varying inertia weight (LHNPSO), oscillating triangular inertia weight PSO (OTIWPSO) and AIWCPSO-S algorithms are conducted by computer simulations. The experiment results show that the presented algorithm gives the most correct and fastest convergence capability.

Highlights

  • When the home-service robot executes its task of object grasping at home, apart from the problems of hardware design, the main problem is still the end-effector issue, which means getting the arm to accurately reach the target location and grasp an object using an appropriate posture

  • We focus on posture control analysis, in which the parameters of the correct object coordinate and the appropriate orientation angles are provided in advance so that the robotic arm can grasp the object without considering the robot vision problem

  • In order to proceed to posture control, the appropriate orientation angle for grasping and the coordinates of the object with respect to the robotic arm should be defined beforehand

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Summary

Introduction

When the home-service robot executes its task of object grasping at home, apart from the problems of hardware design, the main problem is still the end-effector issue, which means getting the arm to accurately reach the target location and grasp an object using an appropriate posture. Nearchou [8] proposed a modified genetic algorithm to overcome the inverse kinematics problem of redundant robot manipula‐ tors. A new PSO algorithm [19] was introduced to resolve the goal of reaching without having an obstacle avoidance problem for a 6-DOF manip‐ ulator of the home-service robot. This paper presents a novel PSO method that is applied to resolve the grasp posture control problems of a 6-DOF robotic arm for the home-service robot in a home environment. Each bird is considered a “particle” in the PSO algorithm and represents a solution for the objective function These moving particles are deter‐ mined by a velocity, which determines the direction and distance of their movement. This section will give the robot’s hardware specification for forward kinematic analysis, and define the position and orientation of the 6-DOF robotic arm

Forward kinematic analysis
Grasp orientation analysis
Artificial Bee Colony and Proposed PSO Algorithm
ABC and GABC
Fitness function for grasping control
Experimental Results
Experimental set-up
Simulation results
Real-time experiments
Conclusions
Full Text
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