Adaptive walking control of quadruped robots based on central pattern generator (CPG) and reflex

This paper presents a central pattern generator （CPG） and vestibular reflex combined control strategy for a quadruped robot. An oscillator network and a knee-to-hip mapping function are presented to realize the rhythmic motion for the quadruped robot. A two-phase parameter tuning method is designed to adjust the parameters of oscillator network. First, based on the numerical simulation, the influences of the parameters on the output signals are analyzed, then the genetic algorithm （GA） is used to evolve the phase relationships of the oscillators to realize the basic animal-like walking pattern. Moreover, the animal＇s vestibular reflex mechanism is mimicked to realize the adaptive walking of the quadruped robot on a slope terrain. Coupled with the sensory feedback information, the robot can walk up and down the slope smoothly. The presented bio-inspired control method is validated through simulations and experiments with AIBO. Under the control of the presented CPG and vestibular reflex combined control method, AIBO can cope with slipping, falling down and walk on a slope successfully, which demonstrates the effectiveness of the proposed walking control method.

Solving position-posture deviation problem of multi-legged walking robots with semi-round rigid feet by closed-loop control

The semi-round rigid feet would cause position-posture deviation problem because the actual foothold position is hardly known due to the rolling effect of the semi-round rigid feet during the robot walking. The position-posture deviation problem may harm to the stability and the harmony of the robot, or even makes the robot tip over and fail to walk forward. Focused on the position-posture deviation problem of multi-legged walking robots with semi-round rigid feet, a new method of position-posture closed-loop control is proposed to solve the position-posture deviation problem caused by semi-round rigid feet, based on the inverse velocity kinematics of the multi-legged walking robots. The position-posture closed-loop control is divided into two parts: the position closed-loop control and the posture closed-loop control. Thus, the position-posture control for the robot which is a tight coupling and nonlinear system is decoupled. Co-simulations of position-posture open-loop control and position-posture closed-loop control by MATLAB and ADAMS are implemented, respectively. The co-simulation results verify that the position-posture closed-loop control performs well in solving the position-posture deviation problem caused by semi-round rigid feet.

Dynamic Walking of AIBO with Hopf Oscillators

More and more biological evidences have been found that neural networks in the spinal cord, referred to as ＂central pattern generators＂ （CPGs）, govern locomotion. CPGs are capable of producing rhythmic movements, such as swimming, flying, and walking, even when isolated from the brain and sensory inputs. If we could build up any models that have similar functions as CPGs, it will be much easier to design better locomotion for robots. In this paper, a self-training environment is designed and through genetic algorithm （GA）, walking trajectories for every foot of AIBO are generated at first. With this acquired walking pattern, AIBO gets its fastest locomotion speed. Then, this walking pattern is taken as a reference to build CPGs with Hopf oscillators. By changing corresponding parameters, the frequencies and the amplitudes of CPGs＇ outputs can be adjusted online. The limit cycle behavior of Hopf oscillators ensures the online adjustment and the walking stability against perturbation as well. This property suggests a strong adaptive capacity to real environments for robots. At last, simulations are carried on in Webots and verify the proposed method.

A Rhythmic Motion Control Method Inspired by Board Shoe Racing for a Weight-Bearing Exoskeleton

To ensure the flexible walking of the weight-bearing exoskeleton robot,most researchers control the exoskeleton to follow the wearer’s movements and provide force to maintain the current dynamic state.However,due to the limitation of sensing information and computing power,it is difficult for the exoskeleton to provide the wearer reasonable and stable force only based on the dynamic model,especially in switching between swing phase and stance phase.Inspired by China’s traditional sport named board shoe racing,a walking control method based on the cooperation of the human and the exoskeleton is proposed in this paper for a lower-limb exoskeleton named PALExo.Under certain conditions,the exoskeleton itself can walk stably depending on the rhythm signals generated by the Central Pattern Generator(CPG).With certain initiative during walking,it can make proper adjustments according to the human movement.With the help of dynamic simulation software and Genetic Algorithm(GA),the optimized CPG parameters are obtained.Impedance control is introduced to increase the comfort of the wearer.The impedance parameters as well as the CPG parameters are tuned in real time based on feedback.The experiments were conducted with PALExo.The results demonstrate that PALExo can effectively assist the wearer walking with a 45-kg payload benefiting from the proposed method.

Development of Minimalist Bipedal Walking Robot with Flexible Ankle and Split-mass Balancing Systems

This paper presents a novel design of minimalist bipedal walking robot with flexible ankle and split-mass balancing systems.The proposed approach implements a novel strategy to achieve stable bipedal walk by decoupling the walking motion control from the sideway balancing control.This strategy allows the walking controller to execute the walking task independently while the sideway balancing controller continuously maintains the balance of the robot.The hip-mass carry approach and selected stages of walk implemented in the control strategy can minimize the efect of major hip mass of the robot on the stability of its walk.In addition,the developed smooth joint trajectory planning eliminates the impacts of feet during the landing.In this paper,the new design of mechanism for locomotion systems and balancing systems are introduced.An additional degree of freedom introduced at the ankle joint increases the sensitivity of the system and response time to the sideway disturbances.The efectiveness of the proposed strategy is experimentally tested on a bipedal robot prototype.The experimental results provide evidence that the proposed strategy is feasible and advantageous.

Simulation of a large-scale linear move irrigator using virtual reality technology

Spray irrigation is one of the effective techniques in saving water and increasing crop yield.Large-scale linear move spray irrigation systems are widely used in China.However,the traditional go-stop-go driving method causes difficulty in controlling the linear move irrigator.A new control method efficient in operation and the consumption of water,electricity,and labor is needed.Because of the difficulty in real-life examination of the designed systems,virtual reality technology was used to simulate the controlling and driving system in this study.Three-dimensional models of the irrigation system components were built at proper sizes.The three-dimensional images of the farmland as well as the mechanical models of the irrigation system were also built following the principles of ground vehicle dynamics.Application programs were developed to simulate the control system and the driving system.Through simulation an optimal control method was found,which was then used in the field test to control the large scale irrigator to move straight forward with an angle error of less than 0.06°.