Jian Chu

Balance motion generation for a humanoid robot playing table tennis

Rapid advancement in the field of humanoid robot has been on-going in the last ten years, however, the common goal that robot can interact with human being to achieve a complicate task remains a difficult problem. We take table tennis playing as a demonstration to study how a humanoid robot shall interact with the environment and human beings and developed a humanoid robot ‘Kong’ that can play table tennis and rally with a human player continuously. This paper focuses on robots stability keeping during table tennis playing. This problem becomes crucial due to the recoil force resulted from large arm acceleration. We introduce an optimal momentum compensation method and a position-based impedance control scheme to generate body motion so that the robot absorb the recoil force and ensure successful hit to the ball. The experimental results demonstrate that the robot is capable to rally with a human player and can act against the recoil force to maintain stability.

An adaptive trajectory prediction method for ping-pong robots

Trajectory prediction is a key issue to a ping-pong robot, many algorithms have been developed. To get more robust and accuracy prediction under different serving conditions, this paper presents a new prediction method. The proposed method establishes two equivalent forms of the dynamic model of flying ball, where the discrete form for state estimation and the continuous form for trajectory prediction. The two forms share the same parameters value. According to force analysis, It is found that the model parameters are deeply related to balls state (position, velocity) . So we train the model parameters offline respect to balls state, instead of setting them to a constant value. This enables the model to be adapted accordingly online. Experimental results show the effectiveness and accuracy of the proposed method for the ball with different velocities.

Impedance Control and its Effects on a Humanoid Robot Playing Table Tennis

This paper proposes an impedance control scheme used on humanoid robots for stability maintenance when the robot is expected to carry out fast manipulatory tasks. We take table tennis playing as an example to study this issue. The fast acceleration required by table tennis rallying will result in an unknown large reaction force on the robot, causing the body to swing back and forth in an oscillating motion and the foot to lose complete contact with the ground. To improve the stability during fast manipulation and in order to resist disturbances due to the reaction force, we introduce impedance control to absorb the impact and decrease the amplitude of body swinging. The systems adjusting time is also reduced and the oscillations are eliminated according to the experimental results, which show the effectiveness of our scheme.

Compliance control for standing maintenance of humanoid robots under unknown external disturbances.

For stable motions of position controlled humanoid robots, ZMP (Zero Moment Point) control is widely adopted, but needs to be integrated with other controllers due to its relatively slow response and the execution error of robots. While CoM (Center of Mass) control is much more directly than ZMP feedback control in the view of rejecting unknown external disturbance. In the meanwhile, we hope the position-based humanoid robot can have the whole body compliance in standing maintenance. So we proposes a CoM compliance controller to achieve stable standing of position controlled humanoid robot under unknown disturbance. The controller uses the concept of force control and integrates virtual model control with admittance control, where an AMPM (Angular Momentum including inverted Pendulum Model)-based virtual model with variable gain is designed to not only generate desired recovery force but also take the GRF (Grand Reaction Force) constraints into account, while an admittance controller is employed to transform the desired force to expected CoM position and body attitude. The experiments were conducted on the humanoid robot `Kong by exerting external force disturbance and changing the slope of the ground to demonstrate the effectiveness and robustness of our method.

Spin observation and trajectory prediction of a ping-pong ball

For ping-pong playing robots, observing a ball and predicting a balls trajectory accurately in real-time is essential. However, most existing vision systems can only provide balls position observation, and do not take into consideration the spin of the ball, which is very important in competitions. This paper proposes a way to observe and estimate balls spin in real-time, and achieve an accurate prediction. Based on the fact that a spinning balls motion can be separated into global movement and spinning respect to its center, we construct an integrated vision system to observe the two motions separately. With a pan-tilt vision system, the spinning motion is observed through recognizing the position of the brand on the ball and restoring the 3D pose of the ball. Then the spin state is estimated with the method of plane fitting on current and historical observations. With both position and spin information, accurate state estimation and trajectory prediction are realized via Extended Kalman Filter(EKF). Experimental results show the effectiveness and accuracy of the proposed method.

Improving the real-time performance of Ethernet for plant automation (EPA) based industrial networks

Real-time Ethernet (RTE) control systems with critical real-time requirements are called fast real-time (FRT) systems. To improve the real-time performance of Ethernet for plant automation (EPA), we propose an EPA-FRT scheme. The minimum macrocycle of EPA networks is reduced by redefining the EPA network frame format, and the synchronization process is modified to acquire higher accuracy. A multi-segmented topology with a scheduling scheme is introduced to increase effective bandwidth utilization and reduce protocol overheads, and thus to shorten the communication cycle significantly. Performance analysis and practical tests on a prototype system show the effectiveness of the proposed scheme, which achieves the best performance at small periodic payload in large scale systems.

Real-time accurate ball trajectory estimation with “asynchronous” stereo camera system for humanoid Ping-Pong robot

Temporal asynchrony between two cameras in the vision system is a usual problem in practice. In some vision task such as estimating fast moving targets, the estimation error caused by the tiny temporal asynchrony will become non-ignorable essentials. This paper will address on the asynchrony in the stereo vision system of humanoid Ping-Pong robot, and present a real-time accurate Ping-Pong ball trajectory estimation algorithm. In our approach, the complex Ping-Pong ball motion model is simplified by a polynomial parameter function of time t due to the limited observing time interval and the requirement of real-time computation. We then use the perspective projection camera model to re-project the balls parameter function on time t into its image coordinates on both cameras. Based on the assumption that the time gap of two asynchronous cameras will maintain a const during very short time interval, we can obtain the time gap value and also the trajectory parameters of the Ping-Pong ball in a short time interval by minimizing the errors between the images of the ball in each camera and their re-projection images from the modeled parameter function on time t. Comprehensive experiments on real Ping-Pong robot cases are carried out, the results show our approach is more proper for the vision system of humanoid Ping-Pong robot, when concerning the accuracy and real-time performance simultaneously.

Flexible Robotic Spine Actuated by Shape Memory Alloy

A flexible robotic spine actuated by shape memory alloy (SMA) can achieve both bending motion and impact absorption, which will allow robots to realize a variety of postures. In this paper, the robotic spine is designed and simplified into a multi-segment dynamic model based on several verified assumptions. The SMA wire is modelled using the Seelecke-Muller-Acenbach theory. An iterative algorithm is developed to address the external forces distributed along the spine and compute the spines bending angle. Based on the dynamic model, we improve the simulation structure and search algorithm to achieve good efficiency and stable solutions. Experiments are conducted to verify the simulation and the results fit the simulation prediction well, with error of less than five degrees. Design optimization with our simulation tool based on several parameters is also discussed in this paper.

Mapbuilding for dynamic environments using grid vectors

This paper addresses the problem of creating a geometric map with a mobile robot in a dynamic indoor environment. To form an accurate model of the environment, we present a novel map representation called the ‘grid vector’, which combines each vector that represents a directed line segment with a slender occupancy grid map. A modified expectation maximization (EM) based approach is proposed to evaluate the dynamic objects and simultaneously estimate the robot path and the map of the environment. The probability of each grid vector is evaluated in the expectation step and then used to distinguish the vector into static and dynamic ones. The robot path and map are estimated in the maximization step with a graph-based simultaneous localization and mapping (SLAM) method. The representation we introduce provides advantages on making the SLAM method strictly statistic, reducing memory cost, identifying the dynamic objects, and improving the accuracy of the data associations. The SLAM algorithm we present is efficient in computation and convergence. Experiments on three different kinds of data sets show that our representation and algorithm can generate an accurate static map in a dynamic indoor environment.

Identification of Abnormal Operating Conditions and Intelligent Decision System for Earth Pressure Balance Shield Machine

In the Earth Pressure Balance shield construction, the soil dug in the capsule is difficult to form the plastic flow state and will cause three abnormal operating conditions including occlusion, caking in the capsule and spewing at the outlet of the dump device. These abnormal operating conditions will then trigger failure in tunneling, cutter-devices damage and even catastrophic incidents such as ground settlement. This paper effectively integrates mechanism of abnormal operating conditions and knowledge of soil conditioning and establishes a uniform model of identification of abnormal conditions and intelligent decision support system based on belief rule-base system. The model makes full use of knowledge of improving the soil, construction experience and data to optimize the model on-line. Finally, a numerical simulation with specific construction data is presented to illustrate the effectiveness of the algorithm.