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In recent years, a great number of top conferences and workshops on artificial intelligence (AI) were held in China, showing Chinese AI plays an important role in the world. Meanwhile, Chinese government announced an ambitious scheme, “New Generation Artificial Intelligence Development Plan,” for the country to become a world leader in AI technologies by 2030. The AI research in China has covered various aspects, ranging from chips to algorithms. This chapter attempts to give an overview of the recent advances of AI research and development in China, as well as some perspectives on the future development of AI in China.

In as much as it is contested, the Belt and Road Initiative (BRI) is also unexplored, underdiscussed, and, as a result, misunderstood. Frequently viewed through the lens of international relations and global economy, the diverse dimensions of collaboration, including business and research-industry clusters, that BRI enhances, tend to be excluded from the analysis. In a similar manner, the role of the Arab Peninsula in the grand strategy underpinning BRI and its implementation is rarely discussed. BRI is a forward-oriented initiative, an attempt to reap benefits of developments and circumstances that are only nascent. This bears two potent implications. First, as China attempts to influence the context in which it operates, it is subject to change itself; the Chinese business sector evolution attests to that. Second, some of China’s not so obvious partners of today, including those in the Arab Peninsula, are about to turn into key interlocutors of tomorrow. BRI taps into opportunities thus created. This chapter elaborates on these issues and, against this backdrop, outlines how the remaining chapters included in this volume add to this discussion.

The purpose of this paper is to generate grinding trajectory of unknown model parts simply and efficiently. In this paper, a method of grinding trajectory generation of hybrid robot based on Cartesian space direct teaching technology is proposed.

This method first realizes the direct teaching of hybrid robot based on 3Dconnexion SpaceMouse (3DMouse) sensor, and the full path points of the robot are recorded in the teaching process. To reduce the jitter and make the speed control more freely when dragging the robot, the sensor data is processed by Kalman filter, and a variable admittance control model is established. And the joint constraint processing is given during teaching. After that, the path points are modified and fitted into double B-splines, and the speed planning is performed to generate the final grinding trajectory.

Experiment verifies the feasibility of using direct teaching technology in Cartesian space to generate grinding trajectory of unknown model parts. By fitting all the teaching points into cubic B-spline, the smoothness of the grinding trajectory is improved.

The whole method is verified by the self-developed TriMule-600 hybrid robot, and it can also be applied to other industrial robots.

The main contribution of this paper is to realize the direct teaching and trajectory generation of the hybrid robot in Cartesian space, which provides an effective new method for the robot to generate grinding trajectory of unknown model parts.