Search Results (15)

Biosphere Reserves (BRs), designated by UNESCO, are uniquely positioned to serve as model territories for sustainable development, as they aim to harmonize biodiversity conservation with the socio-economic vitality and cultural identity of local communities. This work examines the commitment of the Spanish Network of Biosphere Reserves to the United Nations 2030 Agenda and the Sustainable Development Goals (SDGs). Using a survey-based research design, this study assesses the extent to which the reserves have integrated the SDGs into their strategic frameworks and operational practices. It also identifies and analyses successful initiatives and best practices implemented across Spain that exemplify this integration. The findings highlight the need for enhanced awareness and understanding of the 2030 Agenda among stakeholders, alongside stronger mechanisms for participation, cooperation, and governance. The conclusion emphasises the importance of equipping all reserves with strategic planning tools and robust systems for monitoring, evaluation, and accountability. Moreover, the analysis of exemplary cases reveals the transformative potential of sustainability-oriented projects—not only in advancing environmental goals but also in revitalizing local economies and reinforcing cultural heritage. These insights contribute to a broader understanding of how BRs can act as dynamic laboratories for sustainable development and heritage preservation. Full article

During the process of capturing non-cooperative targets in space, space robots have strict constraints on the position and orientation of the end-effector. Traditional methods typically focus only on the position control of the end-effector, making it difficult to simultaneously satisfy the precise requirements for both the capture position and posture, which can lead to failed or unstable grasping actions. To address this issue, this paper proposes a reinforcement learning-based capture strategy learning method combined with posture planning. First, the structural models and dynamic models of the capture mechanism are constructed. Then, an end-to-end decision control model based on the Optimistic Actor–Critic (OAC) algorithm and integrated with a capture posture planning module is designed. This allows the strategy learning process to reasonably plan the posture of the end-effector to adapt to the complex constraints of the target capture task. Finally, a simulation test environment is established on the Mujoco platform, and training and validation are conducted. The simulation results demonstrate that the model can effectively approach and capture multiple targets with different postures, verifying the effectiveness of the proposed method. Full article

To achieve the goals of “carbon peaking and carbon neutrality”, this paper puts forward the connotation and measurement method for the carbon emission intensity of urban industrial land and conducts an empirical study with the Yangtze River Economic Belt (YREB) as an example. We defined the carbon intensity of urban industrial land as the industrial carbon emissions per unit area of land, which is a spatial mapping of urban industrial economic development and carbon spillover and a key indicator for urban and territorial spatial planning oriented towards the “dual carbon” goal. Findings: The carbon emission density of industrial land in the YREB varied greatly between cities and exhibited significant positive spatial autocorrelation. In addition, the geographical pattern and spatio-temporal evolution model of the urban industrial land carbon emission density had a very complex driving mechanism, and different factors had significant synergistic effects. Therefore, it is suggested that while striving towards the goal of “dual carbon”, the government should incorporate the carbon emission density indicator of urban industrial land into the urban and territorial spatial planning system, and based on the threshold of the medium suitable density, they should design differentiated management policies according to concrete urban policies and encourage cooperation among cities to jointly promote carbon emission management of urban industrial land. In policy design, emphasis should also be placed on highlighting the interactive effects of foreign direct investment, fiscal expenditure, and the number of patent authorizations as well as constructing a combination of policies centered around them to better leverage the impacts of globalization, government intervention, and innovation. Full article

Interactions between mobile robots and human operators in common areas require a high level of safety, especially in terms of trajectory planning, obstacle avoidance and mutual cooperation. In this connection, the crossings of planned trajectories and their uncertainty based on model fluctuations, system noise and sensor noise play an outstanding role. This paper discusses the calculation of the expected areas of interactions during human–robot navigation with respect to fuzzy and noisy information. The expected crossing points of the possible trajectories are nonlinearly associated with the positions and orientations of the robots and humans. The nonlinear transformation of a noisy system input, such as the directions of the motion of humans and robots, to a system output, the expected area of intersection of their trajectories, is performed by two methods: statistical linearization and the sigma-point transformation. For both approaches, fuzzy approximations are presented and the inverse problem is discussed where the input distribution parameters are computed from the given output distribution parameters. Full article

The trajectory or moving-target tracking feature is desirable, because it can be used in various applications where the usefulness of UAVs is already proven. Tracking moving targets can also be applied in scenarios of cooperation between mobile ground-based and flying robots, where mobile ground-based robots could play the role of mobile landing pads. This article presents a novel proposition of an approach to position-tracking problems utilizing artificial potential fields (APF) for quadcopter UAVs, which, in contrast to well-known APF-based path planning methods, is a dynamic problem and must be carried out online while keeping the tracking error as low as possible. Also, a new flight control is proposed, which uses roll, pitch, and yaw angle control based on the velocity vector. This method not only allows the UAV to track a point where the potential function reaches its minimum but also enables the alignment of the course and velocity to the direction and speed given by the velocity vector from the APF. Simulation results present the possibilities of applying the APF method to holonomic UAVs such as quadcopters and show that such UAVs controlled on the basis of an APF behave as non-holonomic UAVs during 90° turns. This allows them and the onboard camera to be oriented toward the tracked target. In simulations, the AR Drone 2.0 model of the Parrot quadcopter is used, which will make it possible to easily verify the method in real flights in future research. Full article

Shared energy storage is an energy storage business application model that integrates traditional energy storage technology with the sharing economy model. Under the moderate scale of investment in energy storage, every effort should be made to maximize the benefits of each main body. In this regard, this paper proposes a distributed shared energy storage double-layer optimal allocation method oriented to source-grid cooperative optimization. First, considering the regulation needs of the power side and the grid side, a distributed shared energy storage operation model is proposed. Second, a distributed shared energy storage double-layer planning model is constructed, with the lowest cost of the distributed shared energy storage system as the upper-layer objective, and the lowest daily integrated operation cost of the distribution grid-distributed new energy stations as the lower-layer objective. Third, a double-layer iterative particle swarm algorithm combined with tide calculation is used to solve the distributed shared energy storage configuration and distribution grid-distributed new energy stations’ economic operation problem. Finally, a comparative analysis of four scenarios verifies that configuring distributed shared energy storage can increase the new energy consumption rate to 100% and reduce the net load peak-valley difference by 61%. Meanwhile, distributed shared energy storage operators have realized positive returns. Full article

The trajectory planning and control of multi-agent systems requires accurate localization, which may not be possible when GPS signals and fixed features required for SLAM are not available. Cooperative Localization (CL) in multi-agent systems offers a short-term solution that may significantly improve vehicle pose estimation. CL algorithms have been mainly developed and assessed for planar mobile robot networks due to complexities and singularities in three-dimensional (3D) motion. In this paper, we develop the required singularity-free equations and apply and assess an EKF-based CL for 3D vehicle networks. We assess the performance of CL with respect to the number of simultaneous and redundant measurements. We further assess CL performance with only relative position measurements available. Finally, experiments are performed to validate the proposed algorithms. We further investigate the effect of absolute position measurements in CL. Conclusions: Cooperative localization is an effective method when applied to 3D vehicle networks. However, CL does not improve localization with only relative position measurements, and thus previously reported results for 2D vehicle models were only effective due to relative orientation measurements. Absolute measurement reduces the overall localization errors much more significantly when there has been CL with prior relative position measurements. Full article

The aim of this paper is to design a fuzzy motion control algorithm for a developed monocular vision system based on a cooperative transportation system of two humanoid robots. The control strategies of the cooperation transportation system contain three stages, including object searching, walking toward the transported object, and cooperatively moving the transported object. To have different moving speeds, the gait step size was pre-planned as two different modes, i.e., one of the gaits is selected to let the HR have large variations of motion and another gait is to make the HR with small variations. The fuzzy motion control algorithm is utilized to select the appropriate mode of gait. Both humanoid robots can actively search and move to the front of the target object, then cooperatively lift the target and carry it to the platform. The task of synchronous movement is controlled with fuzzy techniques through the control terminal. From the experimental results, it can be seen that both robots can distinguish the orientation of the target, move to the appropriate position, and then successfully raise the target together. Full article

Multirobot cooperation enhancing the efficiency of numerous applications such as maintenance, rescue, inspection in cluttered unknown environments is the interesting topic recently. However, designing a formation strategy for multiple robots which enables the agents to follow the predefined master robot during navigation actions without a prebuilt map is challenging due to the uncertainties of self-localization and motion control. In this paper, we present a multirobot system to form the symmetrical patterns effectively within the unknown environment deployed randomly. To enable self-localization during group formatting, we propose the sensor fusion system leveraging sensor fusion from the ultrawideband-based positioning system, Inertial Measurement Unit orientation system, and wheel encoder to estimate robot locations precisely. Moreover, we propose a global path planning algorithm considering the kinematic of the robot’s action inside the workspace as a metric space. Experiments are conducted on a set of robots called Falcon with a conventional four-wheel skid steering schematic as a case study to validate our proposed path planning technique. The outcome of our trials shows that the proposed approach produces exact robot locations after sensor fusion with the feasible formation tracking of multiple robots system on the simulated and real-world experiments. Full article

The agrifood industry contributes to sustaining the population and the economic growth in rural areas of Spain. Innovation in the agrifood sector has therefore become a necessity as a means of improving the competitiveness of companies and the territory, thus promoting sustainable rural development in areas currently characterised by social issues such as depopulation. Meeting this need requires the generation of specific knowledge on innovation in the rural agrifood industry to strategically steer the business management of innovation. This study aims to contribute to further improving the competitiveness of the agrifood industry through the interrelation of critical innovation factors in small and medium-sized agrifood enterprises, thus shedding light on the innovation environment of differentiated local products in depopulated rural regions. The qualitative Interpretive Structural Modelling (ISM) methodology was used with the participation of entrepreneurs and experts from the sector. The ISM was applied to a case study in Alcarria Conquense, a Spanish region that embodies the current problems of many rural territories. The results show four factors (cooperation, managerial skills, absorptive capacity, and market orientation) are binding variables with a high power of influence and dependence, and a fifth factor, funding, is the most dependent on the others. The work contributes to the literature by revealing the needs and opportunities for a potential strategic planning of rural development that can positively influence the problems of the region through innovation management in this industry. Full article

The development of 5G network slicing technology, combined with the application scenarios of vehicle–road collaborative positioning, provides end-to-end, large-bandwidth, low-latency, and highly reliable flexible customized services for Internet of Vehicle (IoV) services in different business scenarios. Starting from the needs of the network in the business scenario oriented to co-location, we researched the application of 5G network slicing technology in the vehicle–road cooperative localization system. We considered scheduling 5G slice resources. Creating slices to ensure the safety of the system, provided an optimized solution for the application of the vehicle–road coordinated positioning system. On this basis, this paper proposes a vehicle–road coordinated combined positioning method based on Beidou. On the basis of Beidou positioning and track estimation, using the advantages of the volumetric Kalman model, a combined positioning algorithm based on CKF was established. In order to further improve the positioning accuracy, vehicle characteristics could be extracted based on the traffic monitoring video stream to optimize the service-oriented positioning system. Considering that the vehicles in the urban traffic system can theoretically only travel on the road, the plan can be further optimized based on the road network information. It was preliminarily verified by simulation that this research idea has improved the relative single positioning method. Full article

In this paper, the trajectory planning and position/force coordination control of multi-robot systems during the welding process are discussed. Trajectory planning is the basis of the position/ force cooperative control, an object-oriented hierarchical planning control strategy is adopted firstly, which has the ability to solve the problem of complex coordinate transformation, welding process requirement and constraints, etc. Furthermore, a new symmetrical internal and external adaptive variable impedance control is proposed for position/force tracking of multi-robot cooperative manipulators. Based on this control approach, the multi-robot cooperative manipulator is able to track a dynamic desired force and compensate for the unknown trajectory deviations, which result from external disturbances and calibration errors. In the end, the developed control scheme is experimentally tested on a multi-robot setup which is composed of three ESTUN industrial manipulators by welding a pipe-contact-pipe object. The simulations and experimental results are strongly proved that the proposed approach can finish the welding task smoothly and achieve a good position/force tracking performance. Full article

The decline of inner-city manufacturing industries is a global phenomenon, leaving behind vacant land and brownfield sites in cities. These post-industrial areas with their negative images of dereliction and obsolete urban environments have prompted many cities to implement various redevelopment strategies, among which is the concept of the Urban Entertainment Center (UEC), which combines shopping, recreation, and entertainment, with various public spaces. This study attempts to understand the changes that have been triggered by the revitalization strategy of UEC development in large-scale post-industrial sites in Seoul. Here, Special Planning District (SPD) regulation has been adopted to induce creative and long-term urban developments; however, this has been limited to private high-rise residential buildings. This paper examines two UEC development cases applied along with the SPD in semi-industrial areas for their achievements that differ from former implementations. Our analysis reveals several positive aspects: it provides a sustainable urban infrastructure for the region, overcomes the limitations of the SPD regulation practice, and establishes improved urban environment and design quality oriented toward public interest. The “privatization of planning” has become an issue in redevelopment projects. However, the two UEC precedents that are discussed imply that building cooperative public–private partnerships through a reciprocal process will secure more public benefit overall. Full article

The Community added value of Centres of Expertise (CoE) and European Reference Networks (ERN) is particularly high for rare diseases (RD) due to the rarity of these conditions, which implies both a small number of patients and scarcity of expertise within a single country. Gathering expertise at the European level is therefore, paramount in order to ensure equal access to accurate information, appropriate and timely diagnosis and high quality clinical care and follow up for patients with rare diseases. This applies particularly to rare anaemias due to the high number of different rare diseases that constitute this group. In this context, the European Network for Rare and Congenital Anaemias (ENERCA), co-financed by the European Commission, was created in 2002 with the aim of prevention and management of rare anaemias (RA) and the development and promotion of policies to improve the well-being of European Union citizens. The ENERCA White Book is a position paper, developed as a deliverable of the ENERCA (phase 3) project that intends to contribute to the creation of a ERN in RA (ERN-RA) by preparation of the recommendations and, in particular, the definition of the criteria that CoE, local centres (LC) and their interrelations have to fulfil as healthcare providers. It has been nourished by all the activities that have been performed over the past ten years within the ENERCA framework. The White Book is addressed to authorities in charge of the identifying CoE, as an essential requirement for the official recognition of the ERN, to European and national health authorities, Healthcare centres and health professionals, as well as to all other stakeholders interested in RA. It is also addressed to the patients, as a way to empower their community in this process. One particular characteristic of the White Book is the integration of the three main aspects of a CoE: (a) ethical and legal frameworks to ensure the non-discrimination and non-stigmatisation of rare disease patients across Europe, within their sphere of competencies; (b) clinical and laboratory frameworks for defining technical and quality criteria including scope, general and disease specific elements currently defined as technical and professional standards for the diagnosis, treatment and follow-up of patients with RA; and (c) the expectations patients have of CoE. Conceived as a working tool directed to a broad range of stakeholders, the White book has been designed and structured to be comprehensible even to non-technical and /or non-professional audiences. The reader will find an up-to-date description and epidemiological information on RA as well as the European Union background policies for defining CoE and ERN-RA. A working group was created with experts of different profiles, known as the European Working Group on Rare Anaemias (EGRA). In order to achieve its objectives, the methodology used by EGRA, was characterised by three main principles: Interdisciplinary, European coverage, and evidence-based principles. Work has been developed into four sequential steps: 1. Analysis of the current situation of RA in Europe by healthcare professionals in order to identify the most relevant issues that have to be addressed by a centre in order for it to be recommended as CoE. 2. Preparation of questionnaires to perform surveys on how the relevant issues identified in step 1 can be translated into practical recommendations. 3. Analysis of the questionnaire results by face to face meetings, feedback and consensus evaluation, and 4. Preparation of a report on ENERCA policy recommendations for CoE. This report is presented in a user-friendly format, easy to understand and available through the ENERCA website (www.enerca.org). Several important conclusions can be drawn from the ENERCA White Book, including the importance of laboratories involved in the diagnosis of RA, patient oriented and multidisciplinary care at the CoE, the need for coordination and cooperation within and outside the centre, the provision of information to patients and health professionals and the involvement of public authorities at the national and European levels. Official recognition of this structure and assurance of its long term sustainability will only be achieved if public authorities work hand by hand with both professionals experts in different disciplines and patients. Finally, the ENERCA White book aims to be a practical tool for health authorities of Member States (MS) that are preparing their national directory of formally designated CoE. For this, it is important that MS authorities recognise RA as an important health component to be included within the National Plans or Actions for Rare Diseases. Full article

In this paper, we propose a collision avoidance algorithm for multi-vehicle systems, which is a common problem in many areas, including navigation and robotics. In dynamic environments, vehicles may become involved in potential collisions with each other, particularly when the vehicle density is high and the direction of travel is unrestricted. Cooperatively planning vehicle movement can effectively reduce and fairly distribute the detour inconvenience before subsequently returning vehicles to their intended paths. We present a novel method of cooperative path planning for multi-vehicle systems based on reinforcement learning to address this problem as a decision process. A dynamic system is described as a multi-dimensional space formed by vectors as states to represent all participating vehicles’ position and orientation, whilst considering the kinematic constraints of the vehicles. Actions are defined for the system to transit from one state to another. In order to select appropriate actions whilst satisfying the constraints of path smoothness, constant speed and complying with a minimum distance between vehicles, an approximate value function is iteratively developed to indicate the desirability of every state-action pair from the continuous state space and action space. The proposed scheme comprises two phases. The convergence of the value function takes place in the former learning phase, and it is then used as a path planning guideline in the subsequent action phase. This paper summarizes the concept and methodologies used to implement this online cooperative collision avoidance algorithm and presents results and analysis regarding how this cooperative scheme improves upon two baseline schemes where vehicles make movement decisions independently. Full article