Autonomous Delivery Robots for Last-Mile Logistics: A Comprehensive Review of Navigation, Optimization, and Human Acceptance

Abstract

Last-mile delivery is one of the most expensive and challenging stages of the supply chain due to increasing e-commerce demand, urban congestion, and rising labour costs. Autonomous Delivery Robots (ADRs) have emerged as a promising solution by enabling efficient, contactless, and sustainable package delivery. This review examines recent advancements in ADR technologies, focusing on navigation and localization methods, routing and optimization techniques, operational delivery models, regulatory challenges, sustainability, and human acceptance. A systematic review of 41 publications published between 2018 and 2025 was conducted using major scientific databases. The reviewed studies indicate that technologies such as SLAM, reinforcement learning, and optimization algorithms significantly improve navigation accuracy and delivery efficiency. However, large-scale deployment remains constrained by battery limitations, infrastructure requirements, regulatory issues, and public acceptance. The review also identifies current research gaps and highlights future directions, including multi-robot coordination, artificial intelligence-driven decision-making, smart city integration, and energy-efficient delivery systems. Overall, ADRs have strong potential to transform last-mile logistics while supporting sustainable and intelligent transportation systems.