Fei Meng

Bouncing model for the table tennis trajectory prediction and the strategy of hitting the ball

The bouncing model plays an important role in the trajectory prediction process when the humanoid robots play table tennis. A nonlinear bouncing model based on Momentum Theorem and Moment of Momentum Theorem considering spin of the ball is established to describe the collision between the ball and the table. With the constructed bouncing model, the hitting strategy is discussed to hit the ball the way we expect. The experiments show that with the existing aerodynamic model, we can predict the table tennis trajectory within the error range we expect.

Design and simulation of leg exoskeleton cycling-actuated wheelchair

This article presents a design of novel wheelchair with a leg exoskeleton for locomotion that can be powered by user legs through a cycling action. In addition, the control system is designed with leg-motion assistance for lower limb muscles to perform exercise during wheelchair motion, targeting elderly persons and users with partial hemiplegia. The simulation results characterize the dynamic operation in three possible modes, fully active, fully passive, and user passive–active action.

A master-slave control system for lower limb rehabilitation robot with pedal-actuated exoskeleton

In this paper, a master-slave control system is proposed and implemented for the lower limb rehabilitation robot with pedal-actuated exoskeleton with the aim of coordinating motion of the exoskeleton and wheelchair. The rehabilitation system is designed to let users to walk around and exercise simultaneously. Particularly, the master motion is started by the users intend and the slave motion is activated by the motion of the exoskeleton along with users legs and the motion of the wheelchair. The results of experiments show the proposed method can help users to walk around and exercise their legs simultaneously and effectively.

A Robust Vision Module for Humanoid Robotic Ping-Pong Game

Developing a vision module for a humanoid ping-pong game is challenging due to the spin and the non-linear rebound of the ping-pong ball. In this paper, we present a robust predictive vision module to overcome these problems. The hardware of the vision module is composed of two stereo camera pairs with each pair detecting the 3D positions of the ball on one half of the ping-pong table. The software of the vision module divides the trajectory of the ball into four parts and uses the perceived trajectory in the first part to predict the other parts. In particular, the software of the vision module uses an aerodynamic model to predict the trajectories of the ball in the air and uses a novel non-linear rebound model to predict the change of the balls motion during rebound. The average prediction error of our vision module at the ball returning point is less than 50 mm - a value small enough for standard sized ping-pong rackets. Its average processing speed is 120fps. The precision and efficiency of our vision module enables two humanoid robots to play ping-pong continuously for more than 200 rounds.

Omnidirectional Disturbance Rejection for a Biped Robot by Acceleration Optimization

Biped robots are expected to keep stability after experiencing unknown disturbances which often exist in human daily environments. This paper presents a novel method to reject omnidirectional disturbances by optimizing the accelerations of the floating base of the robot. The optimized accelerations keep the desired external forces within their constraints and generate coordinated whole-body motion to reject disturbances from all directions. The effectiveness of the proposed method is confirmed by simulations with disturbance-rejection scenarios.

A biological humanoid joint controller based on muscle model

It is challenging to design a humanoid robot control framework that maintains high-level motion performance in an unknown environment as this requires complicated sensing capabilities and time-consuming process. On the other hand, basic autonomous motion control in joint space is relatively easier and faster to fulfil dynamic tasks. Based on modeling of human muscles, this paper proposes a biological joint controller developed from biological patterns of muscle activity and dynamics of internal forces. Combining autonomous and synergic control, the controller has the capability of fast active response of environment and autonomous recovery from abnormality. The experiment in Waseda Kyotokagaku Elbow Robot verified the effectiveness of the proposed biological joint controller.

3D smiling facial expression recognition based on SVM

Using Kinect acquired RGB-D image to obtain a face feature parameters and three-dimensional coordinates of the characteristic parameters, and to select the characteristic parameter Facial by Candide-3 model, and feature extraction and normalization. Smile face expression data collection through Kinect, SVM collected to smiley face data classify and output the result of recognition, and the results compared with two-dimensional image of smiling face expression recognition results. Experimental results show that three-dimensional image of smiling face expression recognition accuracy than the two-dimensional image of smiling face. This research has important significance for the research and application of facial expression recognition technology.

A dual-motor joint model for humanoid robots

To make humanoid robots walking fast, its important to improve driving force of their leg joints. Usually, each joint of humanoid robots is driven by a single motor. Dual-motor joint, on the other hand, is one of the candidate solutions to meet the power requirement needed for fast walking. This paper proposed a new dual-motor control model. In the model, two motors are treated as a single control plant instead of two parallel control plants. With the usage of current distributor, the control model can pump different current to each motor freely so as to eliminate the unbalance of the load imposed on each motor. Simulation and experiment show that the proposed model works well under high joint load and it can be used on a fast walking humanoid robot.

Method of Design Optimization and Trajectory Implementation on a Small Cat-Like Robot

In the field of robotics, small cat-like robots, due to its small size, good flexibility, low energy consumption, has become a research trend. Elastic four-bar linkage mechanism (EFLM) with programmable trajectory, good stability, and certain buffer performance, is an excellent choice for driver design of small quadruped robot. We designed a novel miniature cat-like robot, Og-cat, which is optimized in structural features and special parameters compared with other similar quadruped robots. Moreover, we developed a method that can make leg trajectory implement accurately for robots using EFLM. A trajectory realization function is obtained through MATLAB fitting so that the trajectory can be executed precisely. The proposed method has been confirmed on our small quadruped robot Og-cat.

Design and Control of Linkage Exoskeletons in Wheelchair

In this paper, a mechanical design and control method of a leg-exoskeleton are proposed for a new wheelchair for persons with problems in lower limbs. For the mechanical design, a pedal-cycling actuation method is proposed with crank-rocker mechanism driven by one motor with a simple mechanical structure to guarantee the user’s safety. Regarding the master-slave control, the user’s motion intention is detected by force sensors on pedals and it is used as the control message for the leg-exoskeleton motion and wheelchair motion. Experiments are discussed to show the characteristic force during the pedalling action. The experiment results give a good inspiration to optimize the control method.