Intercept Algorithm for Predicting the Position of Passing the Ball on Robot Soccer ERSOW

ERSOW is the name of a wheeled soccer robot that competes in the Kontes Robot Sepak Bola Indonesia (KRSBI). The soccer robot plays a soccer game based on the rules adapted from the human soccer game. The ERSOW team was formed in 2016. Starting in 2017, ERSOW participated in the KRSBI with the Middle Size League (MSL) type. Research in the field of wheeled soccer robots is mostly carried out on robot intelligence, such as how robots detect and look for balls, dribble, pass the ball, avoid opponents, and communicate in teams. This research focuses on the ability that the robot can pass the ball in KRSBI 2020. There are adjustments to the rules for its implementation online where the robot has to pass the ball and score as many goals as possible. The robot's ability to know the direction of ball movement and cut the ball movement or intercept is needed. By utilizing data processing from vision to obtain ball speed data and speed algorithm calculations, the passing ball method has a small chance of missing. Based on the results of experiments that have been carried out, the success of ERSOW in passing using this method is 94.7%.

A smart position optimization scheme for badminton doubles based on human–computer interactive training in wireless sensor networks

In the continuous development process, robot technology based on multimedia interactions has been widely used in aerospace, medical, education and service industries. The relationship between robots and humans is getting closer. The improvement of robot intelligence is a process of continuously learning the outside world. Since 1959, multimedia human–computer interaction technology has provided more and more technical support for human research robots. In this paper, we firstly study the characteristics of badminton competition, including the technical characteristics, tactics characteristics, and the collection requirements about on-site training. The technical description of the badminton doubles station is also completed. Furthermore, in terms of the digitalization of the gait-based sensation, the automated acquisition of the gait technology, the simultaneously with the video, and the high-speed imaging system, the system implement information is integrated. After that, badminton multimedia techniques and tactics are designed based on the extensive statistical analysis. The skills and tactics of athletes are expressed in the form of video, graphics and text. Finally, the operators can carry out the technical and tactical analysis processes through good human–computer interactions. This increases the end user’s game information. The related attention and understanding can strengthen the strength and depth of technical and tactical ability analysis. Thus, we propose the station optimization plan for badminton doubles.

A Smart Position Optimization Scheme for Badminton Doubles Based on Human-computer Interactive Training in Wireless Sensor Networks

In the continuous development process, robot technology based on multimedia interactions has been widely used in aerospace, medical, education and service industries. The relationship between robots and humans is getting closer. The improvement of robot intelligence is a process of continuously learning the outside world. Since 1959, multimedia human-computer interaction technology has provided more and more technical support for human research robots. In this paper, we firstly study the characteristics of badminton competition, including the technical characteristics, tactics characteristics, and the collection requirements about on-site training. The technical description of the badminton doubles station is also completed. Furthermore, in terms of the digitalization of the gait-based sensation, the automated acquisition of the gait technology, the simultaneously with the video, and the high-speed imaging system, the system implement information is integrated. After that, badminton multimedia techniques and tactics are designed based on the extensive statistical analysis. The skills and tactics of athletes are expressed in the form of video, graphics and text. Finally, the operators can carry out the technical and tactical analysis processes through good human-computer interactions. This increases the end user's game information. The related attention and understanding can strengthen the strength and depth of technical and tactical ability analysis. Thus, we propose the station optimization plan for badminton doubles.

The Lyapunov Optimization for Two-Tier Hierarchical-Based MAC in Cloud Robotics

Cloud robotics can largely enhance the robot intelligence by offloading tasks to the cloud dynamically. However, the robots differ in their own hardware configuration such as battery and processing capacity, while the transmission frames are also a mixture of different quality of service (QoS) requirements. As the competition for limited channel resource is inevitable, how to optimize the system performance by effective resource allocation is a key problem. The paper proposes a two-tier hierarchical-based MAC (Two-Tier MAC) which means the classification exists not only in frames but also in robots. The Lyapunov optimization technique is used to maximize the time-averaged quality satisfaction. The experiments show the superior performance of the Two-Tier MAC compared with other MAC protocols especially in overloaded networks. Meanwhile, the system also presents a longer lifetime because the Two-Tier MAC takes energy balance into consideration.

Research on Robot Boxing Movement Simulation Based on Kinect Sensor

In the process of continuous development, robot technology has been widely used in aerospace, medical, education and service industries, and the relationship between robots and people is getting closer and closer. The improvement of robot intelligence is a process of continuous learning of external knowledge. Since the introduction of human-computer interaction technology, it has provided more and more technical support for human research robots. This paper firstly takes Tai Chi as an example, analyzes and deconstructs its standard Tai Chi putter movements, and obtains the corresponding movement parameter information. Then, the human body depth image and bone structure are obtained through the Kinect sensor, and the human joint position data is recorded, and then the coordinate data is sent to the brain robot, thereby realizing the imitation learning of the robot's push movements in Tai Chi. The experimental results show that the proposed method can simulate the practice process of inversion of Tai Chi, and can well analyze the shortcomings in the practice process, and then promote the development of the sport.

Cloud Robotics

Cloud robotics is an emerging field which enables the web enabled robots to access the cloud services on the fly. Cloud Robotics was born by merging robotics with the cloud technologies. The robot intelligence is no more in the robot itself but remotely executed on the cloud. Robot acts as thin-client. There are several frameworks already in development and still growing. With the help of high speed networks using 4G/5G technologies, offloading of computation and storage in cloud is the further step in robotic evolution. This chapter deals the exploration of cloud robotics with its architecture, applications and existing frameworks. Also, existing research carried out is summarized in this chapter. The future challenges are discussed to foresee the opportunities in cloud robotics. It aims for the complete study on how robots leverages the cloud computing.