Urban Robot

This study develops a method for measuring the demand for instant delivery by integrating the YOLOv8 and ByteTrack algorithms to create a model that automates the identification and counting of delivery riders in campus surveillance videos. Combined with survey data, which provided synthesized building-scale and minute-level order information, this data forms the basis for simulation. The study then extracts key parameters of the delivery process and a multi-dimensional performance metrics framework. Using the AnyLogic platform, the study conducts simulations of various scenarios of unmanned last-mile logistics, comprehensively analyzing the potential applications and overall impacts of robots in the campus environment.

The simulation results reveal that unmanned logistics systems offer significant advantages in enhancing delivery efficiency and reducing energy consumption, although its performance in terms of service level is slightly lacking. Measures such as increasing the speed of robots or riders, expanding the scale of robots, adding more delivery hubs, and optimizing the spatial layout of these hubs can significantly enhance delivery efficiency, reduce customer waiting times, and decrease energy consumption. Additionally, to meet the current campus's instant delivery demand, the study suggests deploying at least 40 robots and recommends establishing 4-5 delivery hubs across the campus, with each hub housing 15-20 robots as a cost-effective planning solution. A controlled delivery speed of 13-15 km/h is deemed appropriate for both robots and riders. Further, the study conducted multi-scenario comparisons through simulations and based on the best scenario, planned a future unmanned delivery system for campus. The study proposed a set of planning and design guidelines for an unmanned logistics system tailored to campus environments, addressing key aspects such as delivery zones, routes, and hub designs. Lastly, combining literature and practical cases, the study constructed a framework for analyzing robot characteristics and summarized the challenges they face in urban spaces, proposing corresponding strategies at macro-control rules, meso-system planning, and micro-spatial design levels.

Robots are entering from factories and laboratories into the urban space, to improve its smart governance and service, alleviate the aging pressure, and promote sustainable and resilient urban development. The application of urban robots has become an inevitable trend in the future development of cities. Like other disruptive technologies, its application will reshape urban life and urban space, but the existing research lacks a discussion on its relationship with urban space. Our research defines the concept of “urban robots” and constructs a feature analysis framework to describe the workflow of urban robots, covering its physical, social, and digital attributes, through a systematic literature review of 78 WoS core collection literatures. Based on the framework, this paper further summarizes the characteristics of urban robots, six of their application areas as well as spatial problems they face such as diverse obstacles, lack of structural rules, and a high likelihood of cross interference. Finally, in order to solve the spatial problems faced by urban robots and place some limits on their behaviors, this paper, based on design cases, proposes exploratory strategies for urban space response and coordination, so as to promote thinking about future urban space design.