Qiuguo Zhu

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.

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.

Adaptive Torque and Position Control for a Legged Robot Based on a Series Elastic Actuator

Inspired by biological systems, we seek to achieve natural dynamics and versatile locomotion for hopping or running robots by installing a series elastic actuator (SEA) in the joints due to its compliant property, passive adaptability and energy storage. However, robots equipped with these actuators have drawbacks in terms of substantial delay and limited bandwidth in their position control, especially when a robot has to choose its foothold while it is running at a demanding speed. To solve these problems, compliance control and adaptive position/torque control are introduced to a hopping- legged robot in this paper. The compliant performance of the robot can be improved through the intrinsic property of an SEA with a torque control algorithm. Combining the kinetics model and stochastic model of a 2-DOF robot, an adaptive position control with Kalman Filtering (KF) is developed to provide rapid convergent state estimation of the load on the robotic end-effector by solving the inverse dynamics. Validating the robustness and effectiveness of the proposed algorithm on our hopping-legged robot Tigger, the experimental results show very good position-tracking and disturbance-rejection, as well as flexible interactions while operating in a complex environment.

Vibration suppression based on input shaping for biped walking

The non-rigid behavior of a humanoid robot system will cause vibrations during walking which can affect the walking stability. In this paper, a feed forward controller based on the input shaping method is proposed to reduce such vibrations, which are modeled with second-order processes. Then the corresponding input shapers are designed and applied to the reference ZMP trajectory. The motions generated from the modified referenced ZMP trajectory will yield significantly less vibrations. The effectiveness of our method was validated through experiments on a full-size humanoid robot.

Push recovery for the standing under-actuated bipedal robot using the hip strategy

This paper presents a control algorithm for push recovery, which particularly focuses on the hip strategy when an external disturbance is applied on the body of a standing under-actuated biped. By analyzing a simplified dynamic model of a bipedal robot in the stance phase, it is found that horizontal stability can be maintained with a suitably controlled torque applied at the hip. However, errors in the angle or angular velocity of body posture may appear, due to the dynamic coupling of the translational and rotational motions. To solve this problem, different hip strategies are discussed for two cases when (1) external disturbance is applied on the center of mass (CoM) and (2) external torque is acting around the CoM, and a universal hip strategy is derived for most disturbances. Moreover, three torque primitives for the hip, depending on the type of disturbance, are designed to achieve translational and rotational balance recovery simultaneously. Compared with closed-loop control, the advantage of the open-loop methods of torque primitives lies in rapid response and reasonable performance. Finally, simulation studies of the push recovery of a bipedal robot are presented to demonstrate the effectiveness of the proposed methods.

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.

Average Consensus Analysis of Distributed Inference with Uncertain Markovian Transition Probability

The average consensus problem of distributed inference in a wireless sensor network under Markovian communication topology of uncertain transition probability is studied. A sufficient condition for average consensus of linear distributed inference algorithm is presented. Based on linear matrix inequalities and numerical optimization, a design method of fast distributed inference is provided.

Standing Posture Control of Bipedal Robots with Adaptive Compliance Under Unknown Payload Variations and External Disturbances

When executing tasks, robots are required to demonstrate compliance to unexpected external disturbances or human–robot interactions, and return to the demanded posture when the disturbances or cont...

Stochastic Consensus of a Class of Continuous-Time Multi-Agent Systems with a Leading Agent

A stochastic consensus problem is studied for a class of continuous-time multi-agent systems with a leading agent. The systems have a switching coupling topology driven by a homogeneous Markov process. The unknown coupling functions among agents are nonlinear or even discontinuous. Under some constraints on the unknown coupling functions, a sufficient condition is provided to guarantee stochastic consensus. The condition is in the form of a linear matrix inequality, which is computationally convenient.

Gait analysis of human locomotion based on motion capture system

This paper presents a segmentation method for human locomotion. The research on the rules of human locomotion plays an important role for the analysis of human movement strategy. We collected locomotion data from eighteen volunteers by motion capture system(MCS), and found that the measured stride length and frequency with speed had a mutation in the critical point between walking and running. To solve this problem, a segmentation method is proposed to describe the two gaits motion while the continuous formula is not suitable for using again. Especially, a running formula is proposed by introducing a compression of virtual leg based on the elastic linear inverted pendulum model(ELIPM), which can accurately describe the relationship between stride length, frequency and speed. By experimental comparisons, the proposed method can reduce 77% of the statistical error than Alexanders one, which indicates this method is an effective approach and can uniform the motion rules for human walking and running.