Research on the Integrated Application of Robotics, Blockchain, and Software Engineering in Intelligent Warehousing

Abstract

This paper explores the integrated application of robotics, blockchain, and software engineering in intelligent warehousing, achieving efficient collaboration and credible management. For software engineering and robotics integration, Model-Driven Architecture (MDA) combined with ROS 2 abstracts warehouse robots' environmental perception and motion control modules into independent models, boosting code reuse by over 40% and keeping system response delay within 50ms. To solve robots' poor path optimization and slow algorithm convergence under multiple constraints, an improved genetic algorithm-based path planning method is proposed. It uses grid method for environment construction, improves traditional genetic algorithm with deletion and smoothing operators plus niche method, and comparative experiments show it outperforms others in path length, smoothness, difficulty, and running time. In blockchain-robotics integration, Hyperledger Fabric-based alliance chain is applied to multi-robot task allocation, defining scheduling priority via smart contracts and relying on PBFT. Tests with 100 nodes show task conflict rate below 0.3 % and financial-grade data security (passing NIST SP 800–210). Software engineering's cross-layer framework addresses integration pain points: bottom-layer lightweight Wasm triples contract efficiency; application-layer Coq verifies protocol non-repudiation. This supports blockchain-driven dynamic allocation with 200 transactions/second throughput and stable end-to-end delay within 200ms, greatly enhancing warehousing efficiency.