A Framework for Sustainable Management of Autonomous Ground Robot Fleets

The aim is to explore the delicate balance between human reasoning and the legal requirements for the appropriate supervisory control of robot weapons. We start by examining the limitations of automatic versus aided target recognition and then review some of the relevant psychological literature on reasoning. A new framework is introduced that reframes autonomy/semi-autonomy in terms of levels of supervisory control. This allows for greater transparency in command and control and the allocation of responsibility. Finally, so-called, human supervised autonomy is assessed in terms of the supervisory control framework. Keywords: autonomous weapons, supervisory control, robot weapons, international humanitarian law, reasoning In a world where computing is taking us to new levels of automation, we must ensure that the decision to kill remains firmly under human control. Most new technological artefacts are controlled by computer chips and the technologies of violence are no exception: computer devices are becoming ubiquitous for most modern weapons and guidance control systems. Currently almost all of these weapons are under “supervisory control”, where a computer program mediates human control.1 Humans need to exercise meaningful control over weapons systems to counter many of the problems that arise from automation. The United States Department of Defense points out a number of the potential difficulties with entirely computerising robot weapon: human error, human-machine interaction failures, malfunctions, communications degradation, software coding errors, enemy cyber attacks, infiltration into the industrial supply chain, * Thank you to Maya Brehm, Article 36 and Dr. Amanda Sharkey, Computer Science, University of Sheffield for helpful comments on earlier drafts of this article. 1 Supervisory control stands in contrast to direct human control such as aiming a conventional rifle and pressing the trigger manually. 2 «The exercise of control over the use of weapons, and, concomitant responsibility and accountability for consequences are fundamental to the governance of the use of force and to the protection of the human person». Article 36 (2013) Memorandum for delegates to the Convention on Certain Conventional Weapons (CCW). Downloaded from: http://bitly.com/NJoVG3. Last accessed March 2 2014. To appear in POLITICA & SOCIETA 2014 2 jamming, spoofing, decoys, other enemy countermeasures or actions, unanticipated situations on the battlefield. 3 Even though such difficulties are well known, there is ever-increasing push by states to develop autonomous robot weapons that could move outside the reach of human supervisory control. The US has conducted advanced testing on a number of autonomous weapons platforms such as X-47b – a fast subsonic autonomous jet that can now take off and land on aircraft carriers, the Crusher – a 7 ton autonomous ground robot, and an autonomous hunting submarine. The Chinese are working on the Anjain supersonic autonomous air-to-air combat vehicle. The Russians are developing an autonomous Skat jet fighter. Israel has the autonomous Guardium ground robot and the UK is in advanced testing of the Taranis – a fully autonomous intercontinental combat aircraft. Currently, public reports on the testing of these robot devices have only been about the weapons-carrying platforms and not the weapons systems as a whole. Although autonomous robot platforms can have multiple useful purposes, arming them to select targets and attack them without deliberative human supervision raises serious legal, ethical, technical and international security concerns. The main concern of this paper is to explain the psychological underpinnings and problems with human supervisory control and to emphasise the need for a comprehensive method to ensure that appropriate deliberative human reasoning is utilised. 1. Automatic versus aided target recognition A major problem with weapons systems in which a computer program selects targets and initiates attack is that to identify and select targets requires well-defined target recognition software. Yet current automatic target recognition methods used by the military are not fit for purpose except in narrowly restricted and highly uncluttered environments. Some of examples of the main methods are: 1. Shape detection makes it possible to recognise a tank in an uncluttered environment, such as a sandy desert plain. Medium to high cluttered environments introduce an unacceptably high false alarm rate. It has proved extremely difficult to distinguish between a truck and a tank or any vehicle amongst clutter, such as 3 US Department of Defense, Autonomy in Weapon Systems, Directive 3000.09, November 21 2012. To appear in POLITICA & SOCIETA 2014 3 trees. For example, such systems use feature detection that would have difficulties distinguishing between a smooth overhanging branch and the barrel of a large gun. 2. Thermal imaging detects heat radiating from an object and shows its movement. But it would be difficult for an autonomous system to parse the image and guarantee that it can distinguish between a tank and a school bus. And certainly could not be used to distinguish between a combatant and civilians. 3. Radiation detection is used by loitering munitions, such as the Israeli Harpy, to detect radar signals and determine if they are friendly. If not then the Harpy dive bombs the radar. It is assumed that the radar is part of an anti-aircraft installation, otherwise radar detection doesn’t have any other means to determine the legitimacy

Purpose – Fleet management is a key function in humanitarian organizations, but is not always recognized as such. This results in poor performance and negative impacts on the organization. The purpose of this paper is to demonstrates how the UN High Commissioner for Refugees (UNHCR) managed to substantially improve its fleet management through the introduction of an Internal Leasing Program (ILP), in which headquarters procures vehicles and leases them to field offices. Design/methodology/approach – This paper develops a framework for fleet management based on a longitudinal case study with UNHCR. It compares fleet performance indicators before and after implementation of an ILP. Findings – At UNHCR, vehicle procurement was driven by availability of funding. Fleet management was highly decentralized and field offices had limited awareness of its importance. These systems and behaviors led to major challenges for the organization. The introduction of the ILP positively impacted fleet management at UNHCR by reducing fleet size, average age of fleet and procurement costs. Practical implications – This paper provides fleet managers with a tool for analyzing their fleet. The frameworks and actions described in this paper contain practical recommendations for achieving a well-performing fleet. Originality/value – This paper is the first to analyze fleet management before and after introduction of an ILP. It describes the benefits of this model based on empirical data, and develops frameworks to be used by researchers and practitioners.

One of the missions of the TotalEnergies’ R&D is to pave the way for tomorrow's simpler, streamlined and less expensive facilities. The vision is focused on unmanned installations in which autonomous ground robots are key components. In 2017, the ARGOS (Autonomous Robots for Gas and Oil Sites) Challenge delivered the first prototype of a new generation of autonomous, ATEX-compliant ground robots capable of detecting anomalies. Based on this success, TotalEnergies started a few projects with the aim to introduce and standardize robotics on O&G sites. The first project is the development of a series of autonomous robots, designed to withstand the rough O&G environment for long durations: an inspection robot and an operator robot. The second project is the adaptation of the standard methods of engineering operations for green-field developments as well as preparing the implementation of robots on brownfields. The third one is the development of a specific environment to remotely supervise a fleet of robots operating simultaneously on a same site. A major take away for the success of robotics implementation is increasing the technological readiness as well as usability and acceptance of the whole robotics operation system. This can be verified only through exposure to users in a realistic environment. After each major development, their proper achievement is measured following a robust process of observation in different contexts. An incremental approach for trials was implemented from testing in specific laboratory conditions up to long duration pilots on major installations under the custody of the future users. Those complex tests are a tremendous source of deep insight in understanding robotic operations and allowing the research to be pushed further towards a more practical solution for the petroleum industry. The presentation will highlight the first tangible results from the operational implementation and prototypes testing of robots and the readiness of robotics for Oil and Gas. The experience gained by TotalEnergies in developing Robotics Operations through testing it extensively in various industrial contexts, represents a unique case with this large scale of usages. It was already shared with some of our peers and this paper is a great opportunity to expose to the Oil and Gas industry to our vision of how to prepare the future of unmanned, safe and environmentally friendly operations.

Fleet and revenue management in car rental companies: A literature review and an integrated conceptual framework

The capabilities of autonomous mobile robotic systems have been steadily improving due to recent advancements in computer science, engineering, and related disciplines such as cognitive science. In controlled environments, robots have achieved relatively high levels of autonomy. In more unstructured environments, however, the development of fully autonomous mobile robots remains challenging due to the complexity of understanding these environments. Many autonomous mobile robots use classical, learning-based or hybrid approaches for navigation. More recent learning-based methods may replace the complete navigation pipeline or selected stages of the classical approach. For effective deployment, autonomous robots must understand their external environments at a sophisticated level according to their intended applications. Therefore, in addition to robot perception, scene analysis and higher-level scene understanding (e.g., traversable/non-traversable, rough or smooth terrain, etc.) are required for autonomous robot navigation in unstructured outdoor environments. This paper provides a comprehensive review and critical analysis of these methods in the context of their applications to the problems of robot perception and scene understanding in unstructured environments and the related problems of localisation, environment mapping and path planning. State-of-the-art sensor fusion methods and multimodal scene understanding approaches are also discussed and evaluated within this context. The paper concludes with an in-depth discussion regarding the current state of the autonomous ground robot navigation challenge in unstructured outdoor environments and the most promising future research directions to overcome these challenges.

The urgency to address climate change and achieve net zero targets underscores the critical role of underground infrastructure in considerations of urban resilience and sustainability. This paper leverages insights from the „Road to Net Zero“ (RtNZ) initiative in the UK, integrating advanced methodologies such as carbon optioneering tools and autonomous robotics. By addressing the complexities of underground systems, the research presents a cohesive framework for sustainable urban development and infrastructure management. Drawing on the RtNZ Design Options Framework, the paper explores opportunities to minimize the carbon emissions for four alternative design options for streetworks: trenching, minimum dig techniques, trenchless technologies, and autonomous robotics. Actions in support of carbon reduction form part of a structured pathway to address systemic challenges in subsurface management and highlight the importance of integrating innovative solutions for sustainable infrastructure development. The integration of data-driven tools, such as the RtNZ Optioneering Tool that accounts for all social, environmental and indirect economic consequences of streetworks, combined with advanced thinking from projects such as Mapping and Assessing the Underworld, offers robust methodologies to quantify impacts, mitigate risks, and optimize design decisions. Pipebots, as a future vision, exemplify transformative solutions to subsurface challenges, combining autonomous capabilities with enhanced ecological stewardship. The overarching threads of sustainability, resilience, and health and safety form part of this ‘total value analysis’, which takes a whole subsurface perspective.

Robotic fleet management systems are increasingly vital for sustainable operations in agriculture, forestry, and other field domains where labor shortages, efficiency, and environmental concerns intersect. We present FORMIGA, a fleet management framework that integrates human operators and autonomous robots into a collaborative ecosystem. FORMIGA combines standardised communication through the Robot Operating System with a user-centered interface for monitoring and intervention, while also leveraging large language models to generate executable task code from natural language prompts. The framework was deployed and validated within the FEROX project, a European initiative addressing sustainable berry harvesting in remote environments. In simulation-based trials, FORMIGA demonstrated adaptive task allocation, reduced operator workload, and faster task completion compared to semi-autonomous control, enabling dynamic labor division between humans and robots. By enhancing productivity, supporting worker safety, and promoting resource-efficient operations, FORMIGA contributes to the economic, and environmental dimensions of sustainability, offering a transferable tool for advancing human-robot collaboration in field robotics.

Sustainable Water Quality Management Framework and a Strategy Planning System for a River Basin

Fleet management is a sequential multi-criteria decision problem with uncertainties related to both the information at the time of decision-making, and the outcome of the decision. Structural risk and reliability analyses provide a baseline for decision-making, and can be used to provide input information for a higher-level fatigue analysis framework that takes into account decision criteria, reflecting fleet management strategy, in the decision analyses. A 'top-down' fatigue analysis framework is introduced, where the framework allows the fleet manager to make 'what-if' analyses of the performance of alternative flight task mixes or flight programs. The required measurement data is any fatigue life measures obtained from fatigue-monitoring systems. These are used as evidence in Bayesian inference on fatigue damage parameters needed for higher-level analyses. The framework can be used to assess feasibility and/or rank flight and maintenance programs designed during the flight operations planning phase. The implementation of the fatigue analysis framework requires the development of computer software. Planning of the software development process is under way

Integrated water resource management has been discussed since at least the Civil War; yet, there is still no integrated framework for sustainably managing water. Recognizing this need, the Water Environment Research Foundation (WERF) funded a research project to develop an integrated, conceptual framework for sustainable water resources management. Through WERF funding, this framework was developed over the past four years. Development of the framework was guided by the U.N. Agenda 21, Global Water Partnership, the Enlibra Principles, and Panarchy Theory. The conceptual framework for Sustainable Water Resources Management considers water as a renewable, but finite resource with global and regional constraints. It integrates ecological, economic, and social considerations through institutional and legal/regulatory constructs to move toward sustainable water resources. Implementation of the framework is guided by a process flow?chart that considers both crisis management and proactive management activities. We believe that sustainability is as much an outcome as a goal. If water resources are viewed within a total systems context and monitored, assessed and adaptively managed through time, sustainable water resources are the outcome. This title belongs to WERF Research Report Series ISBN: 9781843397564 (Print) ISBN: 9781780403984 (eBook)

In the era of rapidly changing market and consumer needs, there are dynamic changes in the services offered. This also applies to the car fleet market. Currently, the approach to owning a vehicle is changing to other forms such as rental or subscription. Different types of funding are conducive to changes in the fleet management industry. More and more sophis-ticated services are offered for corporate clients, but also private customers. In the context of these changes, the approach to different aspects of vehicle use is also clarified, including what has been noticeable in recent years, increased interest in road safety, environmental issues and most importantly costs of use and possession of the vehicle. This puts high demands on fleet managers who sustainably need to match the structure of their fleets to the needs and capabilities of their customers while taking into account safety and ecology issues. This is a complicated task that requires decision-making assistance. This article addresses the support of the fleet manager decision, taking into account the sustainable management model. The article aimed to develop a model that takes into account the aspects of safety and ecology from the operator-financier the point of view. The result of the article is to provide a decision-making tool for the selection of vehicles and drivers, taking into account their characteristics to accomplish their tasks. The work presents the problem of fleet management, shows the characteristics of different forms of financing and the impact of market trends on the current approach to these problems. The analysis of safety aspects to the possibility of using different methods affecting its level was then presented. Another element of the article is a mathematical model of the problem of resources assignment for tasks. The developed model is universal and can be used for evaluation and optimisation. To this end, the function of the criterion has been formulated, taking into account the aspects of safety, ecology and financial aspects. It also takes into account the randomness of adverse events and the duration of the remaining appropriations in the out-of-order state. This Model can be used for the risk assessment of the driving staff. The developed model was implemented in the Flexsim environment for a computational example for a trading company. Computational experiments have indicated the correctness of the model and its high application potential, as well as further directions of model development to support complex management processes carried out by fleet managers.

Autonomous robotic vehicles are playing an increasingly important role in support of a wide variety of present and future critical missions. Due to the absence of timely operator/pilot interaction and potential catastrophic consequence of unattended faults and failures, a real-time, onboard health and contingency management system is desired. This system would be capable of detecting and isolating faults, predicting fault progression and automatically reconfiguring the system to accommodate faults. This paper presents the implementation of an integrated health and contingency management system on an autonomous ground robot. This case study is conducted to demonstrate the feasibility and benefit of using real-time prognostics and health management (PHM) information in robot control and mission reconfiguration. Several key software modules including a HyDE-based diagnosis reasoner, particle filtering-based prognosis server and a prognostics-enhanced mission planner are presented in this paper with illustrative experimental results.

Target search using autonomous robots is an important application for both civil and military scenarios. In this paper, a model predictive control (MPC)-based probabilistic search method is presented for a ground robot to localize a stationary target in a dynamic environment. The robot is equipped with a binary sensor for target detection, of which the uncertainties of binary observation are modeled as a Gaussian function. Under the model predictive control framework, the probability map of the target is updated via the recursive Bayesian estimation and the collision avoidance with obstacles is enforced using barrier functions. By approximating the updated probability map using a Gaussian Mixture Model, an analytical form of the objective function in the prediction horizon is derived, which is promising to reduce the computation complexity compared to numerical integration methods. The effectiveness of the proposed method is demonstrated by performing simulations in dynamic scenarios with both static and moving obstacles.

Assessment and implementation of a methodological framework for sustainable management: Lake Kinneret as a case study

Sustainable forest management aims to maintain and enhance the economic, social and environmental value of all types of forests, for the benefit of present and future generations. In Swaziland, despite the existence of numerous local, national, regional and international policies and legislation, sustainable forest management is far fetched. The objective of this paper was to review previous studies on policy reviews, the current status of the non-timber forest products (NTFP) sector, community consultations on resource use and management, user surveys to determine the actual quantities of harvested and utilized edible and medicinal NTFPs, and economic analyses for their direct use value, and inventory and economic valuation of standing stock of various NTFPs. Ulimatelty, this paper has made policy recommendations for the development of a theoretical framework for the sustainable management of NTFPs at the local, national, regional and international levels. This theoretical framework is divided into a set of eleven strategies. These are: Information and social communication; secure rights and access to products from natural forests and woodlands; adoption of innovative policies, revising and updating legislation and elaborating national forestry programmes; development and implementation of national level criteria and indicators for sustainable forest management; project planning and control techniques; local level guidelines for sustainable NTFP management; conservation and financing mechanisms; collaboration and networking between all institutions involved in research and development of NTFPs; institutional strengthening and capacity building; education and training at all levels of community structures; and research and development. Key words: Non-timber forest products (NTFPs), policy, strategy, policies, legislation, economic valuation, sustainable management, assessment, sustainable resource use.