Autonomous Rescue Robots Research Articles

Autonomous Delivery Robots: A Literature Review

Autonomous Delivery Robots: A Literature Review

3D LiDAR Multi-Object Tracking with Short-Term and Long-Term Multi-Level Associations

LiDAR-based Multi-Object Tracking (MOT) is a critical technology employed in various autonomous systems, including self-driving vehicles and autonomous delivery robots. In this paper, a novel LiDAR-based 3D MOT approach is introduced. The proposed method was built upon the Tracking-by-Detection (TbD) paradigm and incorporated multi-level associations that exploit an object’s short-term and long-term relationships with the existing tracks. Specifically, the short-term association leverages the fact that objects do not move much between consecutive frames. In contrast, the long-term association assesses the degree to which a long-term trajectory aligns with current detections. The evaluation of the matching between the current detection and the maintained trajectory was performed using a Graph Convolutional Network (GCN). Furthermore, an inactive track was maintained to address the issue of incorrect ID switching for objects that have been occluded for an extended period. The proposed method was evaluated on the KITTI benchmark MOT tracking dataset and achieved a Higher-Order Tracking Accuracy (HOTA) of 75.65%, marking a 5.66% improvement over the benchmark method AB3DMOT, while also accomplishing the number of ID switches of 39, 74 less than AB3DMOT. These results confirmed the effectiveness of the proposed approach in diverse road environments.

Path Planning of a Mobile Delivery Robot Operating in a Multi-Story Building Based on a Predefined Navigation Tree.

Planning the path of a mobile robot that must transport and deliver small packages inside a multi-story building is a problem that requires a combination of spatial and operational information, such as the location of origin and destination points and how to interact with elevators. This paper presents a solution to this problem, which has been formulated under the following assumptions: (1) the map of the building's floors is available; (2) the position of all origin and destination points is known; (3) the mobile robot has sensors to self-localize on the floors; (4) the building is equipped with remotely controlled elevators; and (5) all doors expected in a delivery route will be open. We start by defining a static navigation tree describing the weighted paths in a multi-story building. We then proceed to describe how this navigation tree can be used to plan the route of a mobile robot and estimate the total length of any delivery route using Dijkstra's algorithm. Finally, we show simulated routing results that demonstrate the effectiveness of this proposal when applied to an autonomous delivery robot operating in a multi-story building.

The impact of customer perceived value on customer satisfaction and loyalty toward the food delivery robot service

研究目的食品配送机器人服务（FDRS）是一种使用自主配送机器人改变移动食品订购的新型服务。尽管FDRS公司在美国各地的服务扩张迅猛, 但对于顾客感知价值、顾客满意度和忠诚度的理解仍有限, 而这对于促进重复销售至关重要。因此, 本研究旨在考察顾客对FDRS的感知价值, 确定影响顾客对FDRS满意度的先决条件, 并调查顾客对FDRS及使用FDRS的餐厅的满意度和忠诚度的影响。研究方法本研究以美国18岁以上并且在过去12个月内使用过FDRS的顾客为样本, 共收集到323份回答。采用描述性统计、确认性因素分析和结构方程模型进行数据分析。研究发现本研究的结果显示功能性、价格和情感价值对顾客满意度有积极影响。当前研究还表明, 顾客满意度对FDRS及餐厅的忠诚度有积极影响。研究创新/价值本研究可以说是首次调查顾客对FDRS购买后的体验, 从而增进对顾客对该服务行为的理解。此外, 本研究采用了来自消费价值理论的多维消费价值方法, 为探索FDRS背景下顾客感知价值、满意度和忠诚度之间的关系提供了一个单一的框架。

Enhancing E-Grocery-Delivery-Network Resilience with Autonomous Delivery Robots

This paper examines the challenges associated with the efficient planning and operation of an E-grocery delivery system using Autonomous Delivery Robots (ADR) during unforeseen events. The primary objective is to minimize unfulfilled customer demands rather than focusing solely on cost reduction, considering the humanitarian aspect. To address this, a two-echelon vehicle routing problem is formulated, taking into account stochastic service times and demands. Two models, namely a deterministic model and a chance-constraint model, are employed to solve this problem. The results demonstrate that the chance-constraint model significantly reduces unmet demands compared to the deterministic model, particularly when the delivery deadline has a broad time window and the ADR/van speed ratio is moderate.

First Time Use of an Autonomous Food Delivery Robot: Effects of Affect and Delivery Scenarios

The objective of the study was to examine the effect of users’ emotions and delivery outcomes from sidewalk autonomous delivery robots on user experience and perception of the robots. Participants’ emotions were induced by specific clips from movies and were measured by a self-report emotion scale. Two delivery scenarios were designed to mimic two extreme delivery outcomes where the delivered food was either on time and as expected or late and not as expected. Results showed that delivery outcomes led to significantly different user experiences, whereas the induced emotions did not. In line with prior research, the current study suggests that the quality of the food delivery service is more important than user emotions in prompting users to want to use the service again and rating the robots more favorably.

Life-cycle analysis of last-mile parcel delivery using autonomous delivery robots

Life-cycle analysis of last-mile parcel delivery using autonomous delivery robots

Empirical study on consumer’s acceptance of delivery robots in France

ABSTRACT The growth of e-commerce has led to an increase in delivery options, and various innovations, such as autonomous delivery robots (ADRs) are being developed to meet the important challenges of the last mile. Currently, in the testing state, consumer acceptance remains relatively unknown. This study aims to identify the factors that affect the level of consumer acceptance of autonomous robotic delivery in urban areas using consumers’ current knowledge of this technology. To answer this question, the factors that negatively or positively influence user acceptance are first determined, and then the validity of the relationships between the factors and user acceptance are tested empirically. The results show that participants of this study are neutral to ADRs, which is reasonable for newly developed technology. Utilitarian factors, such as performance expectancy, are the most important for potential users, followed by social influence, trust in technology, and innovativeness. Price sensibility, perceived risk, and hedonic motivation do not seem to affect the acceptance of ADRs at the current stage of development, whereas effort expectancy shows an atypical negative effect on the behavioural intention to use this technology. However, this study has several limitations that need to be considered, notably the small sample size, which does not allow the generalisation of the results to the French population.

Applied Design and Methodology of Delivery Robots Based on Human–Robot Interaction in Smart Cities

This paper proposes an optimised design of an autonomous delivery robot while adopting the latest technologies from the different branching fields of robotics, artificial intelligence, and tele-communication. As a prospective representation of a user-centric robot design, the proposal is design with the major focus on maximizing users’ satisfaction throughout every human–robot interaction (HRI) touchpoints. By the use of sensor fusion techniques along with the deployment of an image-detection-based technique accompanying the point-cloud-detection-based path-planning methodology, the robot delivery would be optimised with effective path-planning and obstacle avoidance capability. With the extension of 5G connectivity, it is proposed that the real-time status update and video stream would enable greater efficiency in terms of remote monitoring and centralised robot administration.

Consumers' intention to use delivery robots in Iran: An integration of NAM, DOI, and TAM

This study seeks to identify factors influencing the adoption of sidewalk autonomous delivery robots (SADRs) as a green delivery method by shoppers. Accordingly, this study proposes a comprehensive model based on a combination of the norm activation model (NAM), diffusion of innovation (DOI) theory, and technology acceptance model (TAM). The data were collected from 463 Iranian buyers through an online questionnaire. The partial least square (PLS) results revealed that relative advantage, compatibility, and observability positively affected the attitude toward using delivery robots, while complexity negatively impacted this attitude. The observations indicated that problem awareness, ascribed responsibility, and environmental concern positively influenced personal norm. Finally, it was found that personal norm and attitudes toward using delivery robots positively affected the intention to use them. The results of the present work not only provide theoretical contributions to the literature but also can be practically helpful to policymakers.

Review Paper on Anti-Theft Autonomous Delivery Robot for Food and E-Commerce

Abstract: The ongoing development of artificial intelligence and machine learning is enabling robots to become more observant. This advancement allows robots to be utilized in situations where humans may not have control. One example is the use of delivery robots for "last mile" delivery services. These robots can be remotely controlled by an operator in cases where they encounter obstacles. Delivery robots have various applications such as room service, package delivery, food delivery, and hospital deliveries. A research study focused on developing an algorithm that enables autonomous path generation using a GPSbased coordinate system. The algorithm allows the robot to create its own path between its current position and the destination using GPS co-ordinates.

Autonomous Delivery Robot

The Autonomous Delivery Robot is designed with ESP32 Camera module to ensure the complete robotic working of the system. This robot is runs on the 4-wheel drive system and can fly over there with the help of long-range remote controller. The system contains a carrier which carry the packages in it that it can be opened by the recipient only. A delivery robot can be used in different settings such as food, package, medical as well as in hospitality industries also.

Autonomous Delivery Robot

The Autonomous Delivery Robot is designed with ESP32 Camera module to ensure the complete robotic working of the system. This robot is runs on the 4-wheel drive system and can fly over there with the help of long-range remote controller. The system contains a carrier which carry the packages in it that it can be opened by the recipient only. A delivery robot can be used in different settings such as food, package, medical as well as in hospitality industries also.

Sustainable Urban Freight for Energy-Efficient Smart Cities—Systematic Literature Review

Smart cities need energy-efficient and low-emission transportation for people and goods. Most studies focus on sustainable urban-transportation systems for passengers. Freight transportation in cities has increased significantly during the COVID-19 pandemic, leading to greenhouse gases emissions and negative externalities, such as traffic congestion. The purpose of this paper is to identify through a systematic literature review which innovations (hardware and software) applied by logistics service providers (LSPs) in sustainable urban freight (SUF) are suitable to support the transition to energy-efficient smart cities. We propose to classify the existing innovations in last-mile delivery for SUF into categories: (1) urban freight consolidation and/or trans-shipment; (2) the Consumer as a Service Provider (CaaSP); (3) choice of transportation modes. We introduce the concept of CaaSP as an innovative solution in last-mile delivery (LMD), where customers take over some transport operations with the use of smart technologies, and thus reduce the energy demand. We consider the modes of transportation, such as: drones, autonomous delivery robots, autonomous vehicles, cargo bikes (including e-cargo bikes, e-tricycles), electric vehicles (mainly vans), and combined passenger-and-cargo transportation rapid-transit systems. From the analyzed dataset, we find that energy-efficiency in smart cities can be improved by the consolidation of parcels in micro-depots, parcel lockers, and mobile depots. We analyze smart technologies (the Internet of things, big data, artificial intelligence, and digital twins), which enable energy efficiency by reducing the energy demand (fuel) of SUF, due to better operational planning and infrastructure sharing by logistics service providers. We propose a new IEE matrix as an actionable tool for the classification of innovations applied by LSPs in SUF, according to the level of their interconnectivity and energy efficiency. Additionally, this paper contributes to the theory by exploring possible future research directions for SUF in energy-efficient smart cities.

A robust collision prediction and detection method based on neural network for autonomous delivery robots

AbstractFor safe last‐mile autonomous robot delivery services in complex environments, rapid and accurate collision prediction and detection is vital. This study proposes a suitable neural network model that relies on multiple navigation sensors. A light detection and ranging technique is used to measure the relative distances to potential collision obstacles along the robot's path of motion, and an accelerometer is used to detect impacts. The proposed method tightly couples relative distance and acceleration time‐series data in a complementary fashion to minimize errors. A long short‐term memory, fully connected layer, and SoftMax function are integrated to train and classify the rapidly changing collision countermeasure state during robot motion. Simulation results show that the proposed method effectively performs collision prediction and detection for various obstacles.

Observed sidewalk autonomous delivery robot interactions with pedestrians and bicyclists

The recent deployment of sidewalk autonomous delivery robots (SADRs) across university campuses has offered students, staff, and faculty a convenient option for food delivery to their residences or workplaces. However, these low-speed automated food delivery services, which were first commercially deployed on American campuses in early 2019 and continued to offer an important contactless delivery service during the height of the Covid-19 pandemic, traverse campuses on pathways originally designed for pedestrians and bicyclists, creating a potential for conflicts among the different pathway users and potentially unsafe transportation conditions. This study examines one week of field-recorded video from ten locations across the Northern Arizona University campus to help understand the prevalence and severity of SADR-involved interactions with pedestrians and bicyclists. The severity of SADR-involved interactions was quantified by using the surrogate safety measure of post-encroachment time, which was then modeled as a function of conflict- and site-level characteristics to identify predictors of moderate or dangerous conflicts between SADRs and human pathway users. Findings from this study, which provides initial real-world insights into the impacts of SADRs sharing pathways with pedestrians and bicyclists, are intended to help inform facility management strategies capable of supporting the safe introduction of this emerging autonomous freight technology on shared-use facilities in current and potential future settings.

Assessment of readiness of a traffic environment for autonomous delivery robots

Introduction: Autonomous delivery robots are a promising alternative for last-mile delivery. To realise successful implementation of delivery robots in public spaces, it is important to study the interaction between robots and the traffic environment. The traffic environment includes the physical infrastructure and the objects using it like cars and people.Methods: This research proposes an assessment method to determine the readiness of a traffic environment for autonomous delivery robots. A conceptual model is proposed that includes the factors that determine this so-called “roboreadiness”. The two key components of the model are the performance of the robot in the traffic environment and its social acceptance. A real-life experimental test case, expert interviews, and a survey are used to refine and validate the framework.Results: The real-life test case showed for the basic variant a sufficient level both on performance and social acceptance. All other variants such as pillars, road narrowing, and bends did not lead to sufficient performance or social acceptance levels.Discussion: The main outcome of this research is an assessment framework which allows to quantitatively assess traffic performance and social acceptance of sidewalk automated delivery robots. Suggestions for future work include further detailing and elaboration of the approach, scaling up experiments, and researching the possible influence of social acceptance on traffic performance.

Autonomous Delivery Solutions for Last-Mile Logistics Operations: A Literature Review and Research Agenda

The implementation of autonomous delivery solutions in last-mile logistics operations is considered promising. Autonomous delivery solutions can help in tackling urban challenges related to last-mile logistics operations. Urbanization creates higher mobility and transportation demand, which contributes to increased congestion levels, traffic, air pollution, and accident rates. Moreover, mega-trends, such as e-commerce, demand that logistics companies react to increased customer expectations in terms of delivery time and service. Concerning service, electrified autonomous delivery solutions have the potential to operate 24/7 and can help to overcome driver shortages. This paper conducts a systematic literature review. Based on the literature set, a snowballing procedure was applied. Complementary gray literature was included. This work discusses different autonomous delivery solutions such as Autonomous Delivery Robots (ADRs), Unmanned Aerial Vehicles (UAVs), two- or multi-tiered systems, and the concept of passenger and freight integration. The work presents advantages and disadvantages, enabling the comparison of solutions. Furthermore, a research agenda is provided, from which practical-managerial and theoretical implications can be derived. The research agenda can help researchers, manufacturers, businesses, and governmental institutions to prepare for the arrival and subsequent implementation of autonomous delivery services. Various implications related to energy demand, legislation, implementation strategy, training, and risk and safety are presented. The outcome of this work calls for collaboration among various stakeholders, encourages mutual learning, and hints at the importance of national and international development projects.

Autonomous Delivery Robots for Urban Last-mile Logistics Operations: a modified UTAUT framework

Interest in autonomous deliveries among logistics service providers (LSP) is growing. This is due to pressure regarding emission reduction regulations, driving bans inside cities, and growing service demands. Autonomous Delivery Robots (ADR) can form a solution and help to optimize current logistics operations. This work investigates factors that might influence the behavioural intention to use ADR. Focus is on decision-makers of LSP. Data was collected through an online survey. The questionnaire is based on the Unified Theory of Acceptance and Use of Technology (UTAUT). Results provide insights concerning factors shaping the acceptance of ADR for last-mile logistics operations. The factors performance expectancy, facilitating conditions, experience, trust, and perceived risk were found to affect the behavioural intention.

Investigating the Public Acceptance of Autonomous Delivery Vehicles in Hungary

The technological advancement of autonomous vehicles has accelerated in recent days: the number of street tests conducted in the daily traffic of cities is increasing dynamically, and so are the numbers of cities involved, participating developers, and tested vehicles. It can also be observed that not only self-driving cars are being tested on the street now; self-driving buses and trucks are also appearing on public roads, and on the pavements a lesser-known type of vehicle can be found, the so-called autonomous city delivery robots. There are several international studies on the social acceptance of self-driving vehicles, but the vast majority of them focus on self-driving cars. We have little information about how the urban population relates to autonomous delivery robots, which travel on the pavement and can come into much more direct contact with residents than their counterparts that travel on the road or in the air. Our study, by means of netnography and questionnaire research, as well as motion picture sentiment research, analyses Hungarian society's attitude towards self-driving transport vehicles.