Sports robots have become a popular research topic in recent years. For table-tennis robots, ball tracking and trajectory prediction are the most important technologies. Several methods were developed in previous research efforts, and they can be divided into two categories: physical models and machine learning. The former use algorithms that consider gravity, air resistance, the Magnus effect, and elastic collision. However, estimating these external forces require high sampling frequencies that can only be achieved with high-efficiency imaging equipment. This study thus employed machine learning to learn the flight trajectories of ping-pong balls, which consist of two parabolic trajectories: one beginning at the serving point and ending at the landing point on the table, and the other beginning at the landing point and ending at the striking point of the robot. We established two artificial neural networks to learn these two trajectories. We conducted a simulation experiment using 200 real-world trajectories as training data. The mean errors of the proposed dual-network method and a single-network model were 39.6 mm and 42.9 mm, respectively. The results indicate that the prediction performance of the proposed dual-network method is better than that of the single-network approach. We also used the physical model to generate 330 trajectories for training and the simulation test results show that the trained model achieved a success rate of 97% out of 30 attempts, which was higher than the success rate of 70% obtained by the physical model. A physical experiment presented a mean error and standard deviation of 36.6 mm and 18.8 mm, respectively. The results also show that even without the time stamps, the proposed method maintains its prediction performance with the additional advantages of 15% fewer parameters in the overall network and 54% shorter training time.

Load capacity is an important index to reflect the practicability of legged robots. Existing research into quadruped robots has not analyzed their load performance in terms of their structural design and control method from a systematic point of view. This paper proposes a structural design method and crawling pattern generator for a planar quadruped robot that can realize high-payload locomotion. First, the functions required to evaluate the leg’s load capacity are established, and quantitative comparative analyses of the candidates are performed to select the leg structure with the best load capacity. We also propose a highly integrated design method for a driver module to improve the robot’s load capacity. Second, in order to realize stable load locomotion, a novel crawling pattern generator based on trunk swaying is proposed which can realize lateral center of mass (CoM) movement by adjusting the leg lengths on both sides to change the CoM projection in the trunk width direction. Finally, loaded crawling simulations and experiments performed with our self-developed quadruped robot show that stable crawling with load ratios exceeding 66% can be realized, thus verifying the effectiveness and superiority of the proposed method.

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Abstract:The remarkable ability of humans to perform jump maneuvers greatly contributes to the improvements of the obstacle negotiation ability of humans. The paper proposes a jumping control scheme for a bipedal robot to perform a high jump. The half-body of the robot is modeled as three planar links and the motion during the launching phase is taken into account. A geometrically simple motion was first conducted through which the gear reduction ratio that matches the maximum motor output for high jumping was selected. Then, the following strategies to further exploit the motor output performance was examined: (1) to set the maximum torque of each joint as the baseline that is explicitly modeled as a piecewise linear function dependent on the joint angular velocity; (2) to exert it with a correction of the joint angular accelerations in order to satisfy some balancing criteria during the motion. The criteria include the location of ZMP (zero moment point) and the torque limit. Using the technique described above, the jumping pattern is pre-calculated to maximize the jump height. Finally, the effectiveness of the proposed method is evaluated through simulations. In the simulation, the bipedal robot model achieved a 0.477-m high jump.

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.

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The most important feature of this paper is to transform the complex motion of robot turning into a simple translational motion, thus simplifying the dynamic model. Compared with the method that generates a center of mass (COM) trajectory directly by the inverted pendulum model, this method is more precise. The non-inertial reference is introduced in the turning walk. This method can translate the turning walk into a straight-line walk when the inertial forces act on the robot. The dynamics of the robot model, called linear inverted pendulum (LIP), are changed and improved dynamics are derived to make them apply to the turning walk model. Then, we expend the new LIP model and control the zero moment point (ZMP) to guarantee the stability of the unstable parts of this model in order to generate a stable COM trajectory. We present simulation results for the improved LIP dynamics and verify the stability of the robot turning.

SUMMARYA crucial problem is the risk that a manipulator arm would be damaged by twisting or bending during and after contacting a target satellite. This paper presents a solution to minimize the risk of damage to the arm and thereby enhance contact performance. First, a hand-eye servo controller is proposed as a method for accurately tracking and capturing a target satellite. Next, a motion planning strategy is employed to obtain the best-fit contacting moments. Also, an impedance control law is implemented to increase protection during operation and to ensure more accurate compliance. Finally, to overcome the challenge of verifying algorithms for a space manipulator while on the ground, a novel experimental system with a 6-DOF (degree of freedom) manipulator on a chaser field robot is presented and implemented to capture a target field robot; the proposed methods are then validated using the experimental platform.