Yugang Liu

Real-Time Tip-Over Prevention and Path Following Control for Redundant Nonholonomic Mobile Modular Manipulators via Fuzzy and Neural-Fuzzy Approaches

This paper presents a practical method for automatic tip-over prevention and path following the control of a redundant nonholonomic mobile modular manipulator. According to modular robot concept, the mobile platform is treated as a special module attached to the base of the modular manipulator, then an integrated structure is constructed and its dynamic modeling method is performed. A new tip-over stability criterion based on the supporting forces is proposed in consideration of inertia, gravity, and acceleration. An online fuzzy logic (FL) self-motion planner and an adaptive neural-fuzzy controller (ANFC) are presented: The former is used to generate desired self-motions in a real-time manner, and the latter is used to prevent the robot from tipping over and to control the end-effector to follow a desired spacial trajectory at the same time. The proposed algorithm does not need any a priori knowledge of dynamic parameters and can suppress bounded external disturbances effectively. Simulation results for a real robot validate the dynamic modeling method and the controller design algorithm. DOI: 10.1115/1.2229253

Kinematics and tip-over stability analysis for the mobile modular manipulator

Abstract This paper presents a practical method to establish the kinematics model for the mobile modular manipulator. A tough issue is resolved by decomposing a given task into motions performed by both the manipulator and the mobile platform. A direct differentiation method is used to analyse the differential kinematics. Stability analysis of the mobile manipulator is performed to evaluate the possibility of tip-over; some stability criteria are established. Computer simulations are carried on a real mobile modular manipulator, and ideal results are received to show that the theoretical analysis is feasible and correct.

Parameter identification and vibration control in Modular manipulators

The joint parameters of modular manipulators are prerequisite data for effective dynamic control. A method for identifying these parameters using fuzzy logic was devised to study modular redundant robots. Experimental modal analysis and finite element modeling were exploited to model the dynamics. The joint parameters of a nine degrees-of-freedom (9-DOF) modular robot have been identified. In addition, active vibration control based on a neural network and a genetic algorithm were investigated. Ideal control simulation results for a reduced dynamic model of the 9-DOF modular robot were then derived.

Active Vibration Control of a Modular Robot Combining a Back-Propagation Neural Network with a Genetic Algorithm

In this paper, a genetic algorithm based back-propagation neural network suboptimal controller is developed to control the vibration of a nine-degrees-of-freedom modular robot. A finite-element method is used to model the modules of the robot, and the entire system dynamic equation is established using the substructure synthesis method. Then the joint stiffness parameters are identified based on the experimental modal analysis experiment. After modeling the whole structure with the models of the robotic modules and the joint parameters, simulations of the vibration control for the modular robot in several configurations are carried out. It is shown that the control method presented in this paper is effective at suppressing the residual vibrations of the modular robot.

Online fuzzy logic control for tipover avoidance of autonomous redundant mobile manipulators

A redundant mobile manipulator composed of a three-wheeled non-holonomic mobile platform and a N-degrees of freedom (DOF) onboard manipulator is investigated in this paper. Redundancy for such a robot is exploited to avoid tipover via online adjusting self-motions. The dynamic model is established and a new tipover criterion is proposed considering inertia, gravity and acceleration. An online fuzzy logic (FL) self-motion planner and a robust adaptive controller are presented to prevent the robot from tipover without affecting the end-effectors motion tasks. Real experiments for a redundant mobile manipulator demonstrate that the proposed algorithm is effective.

Control of a mobile modular manipulator moving on a slope

A mobile modular manipulator, which is composed of three-wheeled mobile platform and a four-degree of freedom modular manipulator, is investigated. An effective control method is applied to the mobile modular manipulator control in case of moving on a slope. Kinematics model is built up and Eider angles are introduced in the algorithms. Dynamics model is established using constraint Lagrange formulation. A model-based controller is designed for tracking a spatial trajectory in a 3-D space. Computer simulations are performed which will verify the validity of the analytical methodology put out in this paper.

Parameters identification and vibration control for modular manipulators

The joint parameters of redundant manipulators are prerequisite data for effective dynamics control. An identification method via fuzzy theory and Genetic Algorithm has been presented to study modular redundant robots. The Genetic Algorithm is used in the fuzzy optimization expecting to obtain global optimal solutions. Experimental modal analysis and Finite Element Method have been exploited in dynamics modeling. The joint parameters of a 9-DOF modular redundant robot have been identified. Active vibration control has been approached to a simplified 4-DOF modular manipulator by DOF reduction to the 9-DOF modular manipulator.

The identification of joint parameters for modular robots using fuzzy theory and a genetic algorithm

This paper discusses a technique for identifying the joint parameters of a modular robot in order to study the dynamic characteristics of the whole structure and to realise dynamic control. A method for identifying the joint parameters of the structure applying fuzzy logic combined with a genetic algorithm has been studied using a 9-DOF modular redundant robot. A Genetic Algorithm was used in the fuzzy optimisation, which helped to avoid converging to locally optimal solutions and made the results identified much more reasonable. The joint parameters of a 9-DOF modular redundant robot have been identified.

A new task-consistent overturn prevention algorithm for redundant mobile modular manipulators

This paper presents a new algorithm for automatic overturn prevention and path following control of redundant nonholonomic mobile modular manipulators. According to modular robot concept, a new dynamic modeling method is proposed in consideration of interactive motions, nonholonomic constraints and self-motions. Then, an online self-motion planner (SMP) and a robust adaptive neural-fuzzy controller (RANFC) are devised; the former is used to generate desired self-motions in a real-time manner, while the latter is used to prevent the robot from overturning and to control the end-effector to follow a desired spacial trajectory at the same time. The proposed algorithm does not need exact apriori knowledge of dynamic parameters and can suppress bounded external disturbance effectively. Simulation results for a real robot demonstrate that the proposed algorithm is effective.

Dynamics and model-based control for mobile modular manipulators

The dynamic modeling and trajectory following issues are addressed for mobile modular manipulators. Simulations are performed to validate the proposed algorithms.