Baxter Robot Shape Feature Recognition Algorithm Based on Machine Vision

With the rapid development of artificial intelligence and computer technology, Machine Vision (MV) technology has quietly and deeply affected all aspects of our lives. At the same time, Baxter robots are becoming more and more intelligent and automated. MV technology, especially the shape feature recognition algorithm, is applied to the Baxter robot system to provide technical guarantee for accurate and real-time target feature recognition. Based on the subject of "Baxter Robot Shape Feature Recognition Algorithm Based on MV", this paper focuses on the study of shape feature recognition technology. This paper takes Baxter robot as an example to study the key technology of shape feature recognition when the target in the environment is known. This paper designs the Baxter robot vision system, analyzes the system's workflow and functions, and introduces the Baxter robot system modules and related algorithms. In this paper, the algorithm is used to test the shape characteristics of the target object. The results show that the average recognition accuracy rate is 94.37%, and the running time is 11.97ms. From the specific results of target object shape feature detection, the Baxter robot shape feature recognition algorithm based on machine vision achieves real-time and high accuracy of target object shape feature recognition, and has good stability. In practical applications, compared to traditional shape feature recognition algorithms, the Baxter robot shape feature recognition algorithm based on machine vision is more feasible and can effectively assist people in completing specific tasks and targets for shape feature recognition in practical applications.