In robotic inspection of aviation parts, achieving accurate pairwise point cloud registration between scanned and model data is essential. However, noise and outliers generated in robotic scanned data can compromise registration accuracy. To mitigate this challenge, this article proposes a probability-based registration method utilizing Gaussian Mixture Model (GMM) with local consistency constraint. This method converts the registration problem into a model fitting one, constraining the similarity of posterior distributions between neighboring points to enhance correspondence robustness. We employ the Expectation Maximization algorithm iteratively to find optimal rotation matrix and translation vector while obtaining GMM parameters. Both E-step and M-step have closed-form solutions. Simulation and actual experiments confirm the method's effectiveness, reducing root mean square error by 20% despite the presence of noise and outliers. The proposed method excels in robustness and accuracy compared to existing methods.

Computing specialist Blaize has agreed a strategic partnership with Accton, a premier provider of networking and communications solutions, to bring edge AI computing to the AI inspection market. The Accton Smart Automated Optical Inspection (AOI) solution will utilize the Blaize Pathfinder P1600 Embedded System on Module (SoM) to add visual AI production line inspection for assembly, manufacturing, packaging, and appearance activities. Colby Chou, IoT business unit head of Accton, says: "We are pleased to partner with Blaize to provide our customers with a cost-effective AI inspection service. Our solution helps our customer reduces up to 85 percent of the operators' workload and significantly improves product quality. The Accton product Pallas, uses Blaize's P1600 SoM, leveraging the programmability and efficiency benefits of the Blaize Graph Streaming Processor (GSP) architecture. The SoM is ideal for rugged and challenging environments and offers the processing power, low latency, and energy efficiency crucial for AI inferencing workloads at the edge and the inherent stringent inspection requirements. Accton will be able to implement computer vision applications and new AI inferencing solutions across a range of edge smart vision use cases using the Blaize architecture. Dinakar Munagala, co-founder and CEO of Blaize, says: "Blaize looks forward to providing Accton with a solution that enables stricter quality standards, higher yield, and more efficient manufacturing and inspection processes.

Engineering giant Rolls-Royce has made an ethical artificial intelligence (AI) 'breakthrough', which it believes could contribute to gaining society's trust in the technology on the path to'Industry 5.0'. The firm has unveiled a workable, peer-reviewed AI ethics framework, which is a method that any organization can use to ensure the decisions it takes to use AI in critical and non-critical applications are ethical. The framework, which has been reviewed by several big tech firms -- as well as experts in the automotive, pharmaceutical, academic, and government sectors -- will be published under Creative Commons license this year. The framework includes a step-by-step process for ensuring the outcomes of AI algorithms can be trusted. A five-layer checking system focuses on the outputs of algorithms, not the algorithms themselves, which are constantly changing.