Toward the Deployment of an Autonomous Last-Mile Delivery Robot in Urban Areas: The Ona Prototype Platform

Autonomous inspection robots have emerged as pivotal assets in enhancing operational efficiency and safety within industrial facilities. This paper explores the challenges and opportunities in scaling the deployment of such robots across diverse industrial environments. Firstly, we delve into the technological advancements driving the evolution of autonomous inspection robots, including sensor integration, machine learning algorithms, and real-time data processing capabilities. These advancements enable robots to navigate complex environments, detect anomalies, and perform detailed inspections with high accuracy. However, scaling the deployment of autonomous inspection robots presents multifaceted challenges. These include the need for robust infrastructure to support fleet management, efficient recharge, and seamless integration with existing industrial systems. Additionally, ensuring compliance and addressing cybersecurity concerns are imperative for widespread adoption. Despite these challenges, the benefits of scaling autonomous inspection robots are substantial. Enhanced operational efficiency, reduced downtime, and improved worker safety are among the primary advantages. Moreover, by leveraging data collected by these robots, industries can make data-driven decisions, optimize maintenance schedules, and prevent costly equipment failures. In conclusion, while scaling autonomous inspection robots in industrial facilities presents complex challenges, the potential benefits outweigh the hurdles. By addressing these challenges through interdisciplinary collaboration and technological innovation, the widespread deployment of autonomous inspection robots can revolutionize industrial operations.

This paper investigates the administrative, criminal and civil aspects of Italian law in order to find out whether and how current legal regulations impact on robot deployment in urban environments. The paper is based on a case study. The objects of this study are two autonomous mobile robots designed to carry out urban hygiene services in pedestrian areas. The paper points out a major problem in Italian law — the lack of legal qualification for autonomous mobile robots operating on public roads. On the contrary, at present, no relevant implications are identified with regard to Italian criminal and civil law. As a matter of fact, although autonomous, the robots that are at the center of this study can still be considered as properties and, therefore, are excluded from any personal liability in case of damage to people or things.

A scenario-based feasibility analysis of autonomous robot deliveries

As autonomous robots become more common in urban environments, understanding interactions with pedestrians is crucial for ensuring smooth human-robot coexistence. Serve Robotics, a leader in sustainable urban logistics, operates autonomous sidewalk robots in West Hollywood, California, USA delivering food and packages. These robots, guided by sensors and AI, navigate pedestrian-heavy sidewalks. Their presence raises questions about how pedestrians adjust their walking paths to accommodate the robots. This preliminary field study was designed to gather initial insights into these behaviors, laying the groundwork for a larger, statistically significant study to be conducted in the future.Guided by Proxemics Theory, which examines how individuals manage personal space, this study investigates pedestrian responses to Serve Robotics’ delivery robots. The research question focuses on how pedestrians modify their walking paths when encountering these robots. By documenting observable changes in pedestrian movements—such as veering, slowing down, stopping, or moving closer to the edge of the sidewalk or street—the study identifies patterns influenced by environmental factors like sidewalk width, pedestrian density, and proximity to the robot.Conducted as a preliminary observational field study, the researcher acted as a non-participant observer, documenting interactions between pedestrians and robots in real-world conditions on West Hollywood’s sidewalks. Data were collected on key behaviors, including deviations in path, stops, and speed changes in response to robot movements. Additionally, environmental factors such as time of day, weather, and pedestrian density were recorded. Video recordings, with appropriate consent signage, were used to analyze specific pedestrian behaviors and accurately measure deviations from original paths.This preliminary study utilized both quantitative and qualitative methods. The quantitative analysis specifically measured the frequency and degree of swerving, where pedestrians veered off their original walking path. It also tracked the number of stops or pauses pedestrians made in response to the robots, as well as changes in walking speed, such as slowing down or speeding up when approaching the robots. Additionally, the study recorded proximity of pedestrians to the robots, quantifying how close they allowed the robots to come before altering their path. Data were collected under various conditions, including sidewalk width (narrow versus wide) and pedestrian density (low, moderate, or high). These metrics helped identify behavioral patterns, such as whether narrower sidewalks or faster-moving robots resulted in more significant path deviations or stopping. Qualitative thematic analysis categorized pedestrian responses—such as avoidance, curiosity, or neutrality—based on observational data.Findings from this initial study provide important insights into how autonomous robots impact pedestrian traffic flow. Key behavioral trends identified in this phase of the research can inform the design of human-centered robots that navigate urban environments without causing pedestrian discomfort or creating bottlenecks. Serve Robotics and similar organizations may benefit from adjusting robot speed and proximity to pedestrians or implementing signaling mechanisms to reduce pedestrian path alterations. Insights also suggest potential municipal policies regarding where and how robots should operate on sidewalks to minimize disruptions.Initial findings underscore the need for more extensive research to develop a fuller understanding of pedestrian responses to autonomous robots. A larger study will build on the groundwork established here, aiming to help optimize the design and integration of autonomous systems into public spaces, enhancing pedestrian experiences and advancing the adoption of autonomous technologies. The findings from both this preliminary research and a future larger study will contribute significantly to the broader Human-Robot Interaction field and inform the development of robotic systems designed for more seamless interaction in real-world settings.

To resolve challenges arising from traditional truck-based delivery systems, the integration of autonomous robots into last-mile delivery operations has recently received attention as a promising solution. This study addresses a hybrid truck-robots last-mile delivery system that encompasses both homogeneous and heterogeneous robots. To discuss battery management strategies for robots returning after rendezvousing with a truck, we propose mixed-integer linear programming models offering two options: battery recharging and battery swapping. We explore optimal solutions for truck and robot routes, as well as various robot combinations aimed at minimizing total delivery time. Additionally, we present a three-phased iterative heuristic algorithm designed to effectively solve large-sized problems. The proposed models are validated with application to Southern District, Ulsan, in the Republic of Korea, and Rapid City, South Dakota, in the U.S., serving as examples of urban and rural areas, respectively. Our findings demonstrate that the proposed truck-robots system, particularly with the battery-swapping option, can achieve up to a 50% reduction in total delivery time compared with traditional truck-only delivery systems, applicable to both urban and rural areas. Furthermore, our results underscore the importance of long driving range for the robots in urban areas for enhancing delivery system performance. We also conduct a sensitivity analysis to examine the impact of the following factors on delivery system performance: customer node size, robot speed, number of robots, and various robot ratios. This study helps fill the gap in the literature concerning hybrid truck-robot delivery systems, with implications for improving delivery efficiency and reducing total delivery time in urban areas.

While robots are still absent from our homes, they have started to spread over battlefields. However, the military robots of today are mostly remotely controlled platforms, with no real autonomy. This paper will disclose the obstacles in implementing autonomy for such systems, by answering a technical question: “What level of autonomy is needed in military robots and how and when might it be achieved?”, followed by a techno-legal one; “How to implement the rules of humanitarian law within autonomous fighting robots, in order to allow their legal deployment?”The first chapter scrutinizes the significance of autonomy in robots and the metrics used to quantify it, which were developed by the US Department of Defense.The second chapter focuses on the autonomy of ‘state-of-the-art’ robots (e.g.; Google’s self-driving car, DARPA’s projects, etc) for navigation, ISR or lethal missions. Based on public information, we will get a hint of the architectures, the functioning, the thresholds and technical limitations of such systems. The bottleneck to a higher autonomy of robots seems to be their poor ‘perceptive intelligence’. The last chapter looks to the requirements of humanitarian law (rules of ‘jus in bello’/rules of engagement) to the legal deployment of autonomous lethal robots on the battlefields. The legal and moral reasoning of human soldiers, complying with humanitarian law, is a complex cognitive process which must be emulated by autonomous robots that could make lethal decisions. However, autonomous completion of such ‘moral’ tasks by artificial agents is much more challenging than the autonomous implementation of other tasks, such as navigation, ISR or kinetic attacks. Given the limits of current Artificial Intelligence, it is highly unlikely that robots will acquire such 'moral' capabilities anytime soon. Therefore, for the time being, the autonomous weapon systems might be legally deployed, but only in very particular circumstances, where the requirements of humanitarian law happen to be irrelevant.

Over the past decades, autonomous robots have embedded themselves into human lives in various forms. Although there have been limited number of research studies in this discipline, yet the results of scholars’ studies reveal that humans especially older adults and people with disabilities have benefited from the use of robots in their daily lives. Over the next decades, number of elderly will be growing; therefore, there will be a high demand for assistive robots to enhance mobility and promote independence. The topic to what extend assistive robots should be empowered in daily life is of great concern in robotic discipline. Robot ethics have a dominant role in forming norms for design, use, disposal, and deployment of assistive robots. This paper reviews design ethics of assistive and autonomous medical robot for elderly and disabled.

Detecting and identifying signboards on their route is crucial for all autonomous and semi-autonomous vehicles, such as delivery robots, UAVs, UGVs, etc. If autonomous systems interact more with their environments, they have the ability to improve their operational aspects. Extracting and comprehending textual information embedded in urban areas has recently grown in importance and popularity, especially for autonomous vehicles. Text detection and recognition in urban areas (e.g., store names and street nameplates, signs) is challenging due to the natural environment factors such as lighting, obstructions, weather conditions, and shooting angles, as well as large variability in scene characteristics in terms of text size, color, and background type. In this study, we proposed three stages text detection and recognition approach for outdoor applications of autonomous and semi-autonomous mobile robots. The first step of the proposed approach is to detect the text in urban areas using the "Efficient And Accurate Scene Text Detector (EAST)" algorithm. Easy, Tesseract, and Keras Optical Character Recognition (OCR) algorithms were applied to the detected text to perform a comparative analysis of character recognition methods. As the last step, we used the Sequence Matcher to the recognized text values to improve the method's impact on OCR algorithms in urban areas. Experiments were held on the university campus by an 8-wheeled mobile robot, and a video stream process was carried out through the camera mounted on the top of the mobile robot. The results demonstrate that the Efficient And Accurate Scene Text Detector (EAST) text detection algorithm combined with Keras OCR outperforms other algorithms and reaches an accuracy of 91.6%

The deployment of autonomous delivery robots in urban environments presents unique challenges in navigating complex traffic conditions and interacting with diverse road and sidewalk users. Effective communication between robots and road and sidewalk users is crucial to address these challenges. This study investigates real-world encounter scenarios where delivery robots and road and sidewalk users interact, seeking to understand the essential role of communication in ensuring seamless encounters. Following an online ethnography approach, we collected 117 user-generated videos from TikTok and their associated 2,067 comments. Our systematic analysis revealed several design opportunities to augment communication between delivery robots and road and sidewalk users, which include facilitating multi-party path negotiation, managing unexpected robot behaviour via transparency information, and expressing robot limitations to request human assistance. Moreover, the triangulation of video and comments analysis provides a set of design considerations to realise these opportunities. The findings contribute to understanding the operational context of delivery robots and offer insights for designing interactions with road and sidewalk users, facilitating their integration into urban spaces.

Urban logistics, especially the last mile delivery, is a major urban challenge due to the high density in cities and the use of diesel-powered freight vehicles, resulting in traffic congestion and other negative impacts such as air and noise pollution. With the rise of e-commerce and customer expectation of express delivery, the metropolitan areas are seeking innovative ways to better manage urban freight movement and create an efficient and environment friendly transportation system. Information and communication technology advancement is ushering in a new era of mobility, changing the way people and goods move. Traditionally, freight movement takes the so-called hub-and-spoke delivery model. While the hub-and-spoke model is proven efficient with the economies of scale, it is ill-suited for fulfilling the increasing demand for same-day and even one-hour delivery in urban areas with the inflexible structure and is restricted by the hub capacity. Using real-time information technology for speedy coordination, crowdshipping brings reduction in the transportation costs for the last mile. Crowdshipping provides a feasible alternative in the first and last mile deliveries, provides flexibility of delivery time windows and uses a variety of transport modes for the delivery, for e.g. personal automobiles, taxis, bicycles, cargo cycles, walking etc. In Chapter 3 of this dissertation, an empirical investigation is presented of an existing crowdsourcing delivery company with respect to the operational factors such as parcel size, delivery distance, demand frequency and distribution, the user characteristics including customer and driver profiles, and the pricing model. Both quantitative and qualitative analyses are performed to shed light on the market demand trending and growth opportunities in crowdsourcing deliveries. Another solution to reducing truck trips into busy urban centers is the use of Automated Parcel Station (APS). APS is an automated parcel collection (and sometimes dispatch as well) station located in public spaces. For the ease of access, these APS’ are located at shopping centers, transit stations, gas stations, etc. Parcel recipients travel on foot or by car to collect their parcels from an APS. In Chapter 4 of this dissertation, we propose, formulate, and evaluate a new and innovative delivery paradigm where the last-mile demand fulfilment is done through Microhubs with Crowdshipping (M+C). In this paradigm, an urban service area is divided into a number of smaller service zones (e.g., by zipcode). Within each zone, there is a microhub to temporarily store inbound and outbound parcels of small to medium size. These parcels are collected or distributed by automobile or bicycle crowdshippers between customers (shippers and end receivers) and the zonal microhub. Commercial trucks are dispatched periodically to visit the microhubs in the service area to transfer parcels to their respective destination microhubs. Though, an initiative involving microhubs and dedicated freight bikes has been field tested recently in the Citylab project in Europe for the first time, the performance of a microhubs and crowdshipping paradigm has not been analytically assessed before this dissertation. In Chapter 5 we show that the proposed M+C paradigm is a Many-to-Many Split Pickup and Delivery Problem (M-MSPDP) for truck routing between microhubs. We present a general formulation of M-MSPDP and a Maximum Split-Benefit with Tabu Search (MS-BTS) heuristic to solve the large-scale M-MSPDP. MS-BTS is evaluated with the exact solution methods and other existing heuristics. We further apply the MS-BTS heuristic to solve for two applications of the M-MSPDP: parcel pickup and delivery among parcel stations (i.e., M-MSPDP-FPD) and bike rebalancing in a bike-sharing system (i.e., M-MSPD-OC). The computation time of MS-BTS is considerably improved over the other methods while maintaining a comparable level of the solution quality. Lastly, Chapter 6 considers a futuristic delivery paradigm where all stages of the last-mile demand fulfillment are handled without any involvement of human factor, including for parcel loading/unloading, sorting and transportation between hubs and the customers. This Chapter presents a brief commentary on the impacts of such a proposed delivery paradigm.

In this paper, we will compare two solution options to determine whether the deployment of an autonomous mobile robot will be a beneficial investment for a company not only in terms of cost, time, and manpower savings, but also in terms of efficiency and reliability in the implementation of selected logistics processes to ensure the smooth running of production. In this paper, we would like to analyse the technology in terms of functions, carrying capacity, and interconnection within the infrastructure in the enterprise. The logistics processes from material order to export to the final customer will be analysed when an automatically controlled robot is deployed. One of the solutions discusses the use of personnel and material handling equipment (tractor with transport kit). The second solution discusses the deployment of the robot and selected logistics processes. The paper concludes with a summary of both options in terms of time, cost, and efficiency of the solution.

The deployment of robots in dynamic, complex and uncertain environments populated by people is gaining more and more attention, from both research and application perspectives. The new challenge for the near future is to deploy intelligent social robots in public spaces to make easier and safer the use of these spaces. In this paper, we provide an overview of the COACHES project which addresses fundamental issues related to the design and development of autonomous robots to be deployed in public spaces. In particular, we describe the main components in which Artificial Intelligence techniques are used and integrated with the robotic system, as well as implementation details and some preliminary tests of these components.KeywordsSoftware ArchitectureMarkov Decision ProcessTabu ListShopping MallPlan FailureThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

To bring cutting edge robotics from research centres to social environments, the robotics community must start providing affordable solutions: the costs must be reduced and the quality and usefulness of the robot services must be enhanced. Unfortunately, nowadays the deployment of robots and the adaptation of their services to new environments are tasks that usually require several days of expert work. With this in view, we present a multi-agent system made up of intelligent cameras and autonomous robots, which is easy and fast to deploy in different environments. The cameras will enhance the robot perceptions and allow them to react to situations that require their services. Additionally, the cameras will support the movement of the robots. This will enable our robots to navigate even when there are not maps available. The deployment of our system does not require expertise and can be done in a short period of time, since neither software nor hardware tuning is needed. Every system task is automatic, distributed and based on self-organization processes. Our system is scalable, robust, and flexible to the environment. We carried out several real world experiments, which show the good performance of our proposal.

Scheduling last-mile deliveries with truck-based autonomous robots

Logistics has long been important in an industrial society. Compared with the traditional structure of distribution, which requires freight to be delivered mostly to warehouses or retail stores, customers now often prefer packages to be delivered to their residences, especially after the delivery challenges during the COVID-19 pandemic. The delivery of parcels to urban residential areas increases the challenge due to the amount of delivery volume, tight delivery schedules, and continuously changing delivery conditions. Last-mile delivery tries to address the challenges, taking advantage of the available automation, sensor and communication technologies, and people’s attitudes toward parcel delivery for the benefit of all stakeholders. Various approaches to last-mile delivery have been proposed and analyzed in the literature. This paper reviews the recent literature on vehicle routing for last-mile delivery. The review identified four major categories: crowdshipping, parcel lockers, delivery by sidekicks, and delivery to optional points. The nature of the problems is discussed in five aspects: fleet capacity, time window, fleet option, dynamism of input, and stochastic parameters. The review identifies the achievements and limitations of the research in the areas and proposes a future research agenda.