A multilayer scheme is here proposed to implement coordinated control of a group of mobile robots. Specifically, a trajectory tracking controller is proposed to coordinately guide a platoon of robots, with an obstacle deviation subsystem based on virtual forces and mechanical impedance implemented in each robot. Such a controller is firstly designed for groups of three robots and then generalized to larger groups ($$n>3$$n>3 robots), by proposing a modular structure based on the concatenation of triangular modules, composing a polygon of $$n$$n sides (one of the designed controllers is adopted to guide each module). The stability of the closed-loop control system is also proven for each individual control system, based on the theory of Lyapunov, taking into account the saturation of the control signals, adopted to prevent the saturation of the robot actuators. Based on such a proof, a conjecture that the whole control system is stable is presented, which is supported by several simulated and experimental results, some of which are presented, thus validating the proposed control structure.
The number of people that intentionally avoid the news is growing. This could have several personal and societal implications. Previous research exposed various motives to avoid news, which lead to different manifestations of news avoidance, and consequently different implications. However, so far less is known about the differences in news avoidance types. In this study, we aim to explore different profiles of news avoiders beyond demographics, based on their motives to avoid news, values in life and personality traits. We analyze how this relates to background characteristics, the degree of news avoidance (occasional, regular, consistent), and news consumption. We rely on a survey conducted in The Netherlands (N = 2798) in March 2022. We conducted a Latent Profile Analysis and found seven news avoiders’ profiles: (1) interested occasional avoider; (2) emotive occasional avoider; (3) critical occasional avoider; (4) status-driven occasional avoider; (5) skeptical frequent avoider; (6) news outsider; and (7) convinced frequent avoider. This provides a nuanced picture of news avoidance.
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This PD project aims to gather new knowledge through artistic and participatory design research within neighbourhoods for possible ways of addressing and understanding the avoidance and numbness caused by feelings of vulnerability, discomfort and pain associated with eco-anxiety and chronic fear of environmental doom. The project will include artistic production and suitable forms of fieldwork. The objectives of the PD are to find answers to the practice problem of society which call for art that sensitises, makes aware and helps initiate behavioural change around the consequences of climate change. Rather than visualize future sea levels directly, it will seek to engage with climate change in a metaphorical and poetic way. Neither a doom nor an overly techno-optimistic scenario seem useful to understand the complexity of flood risk management or the dangers of flooding. By challenging both perspectives with artistic means, this research hopes to counter eco-anxiety and create a sense of open thought and susceptibility to new ideas, feelings and chains of thought. Animation and humour, are possible ingredients. The objective is to find and create multiple Dutch water stories, not just one. To achieve this, it is necessary to develop new methods for selecting and repurposing existing impactful stories and strong images. Citizens and students will be included to do so via fieldwork. In addition, archival materials will be used. Archives serve as a repository for memory recollection and reuse, selecting material from the audiovisual archive of the Institute of Sound & Vision will be a crucial part of the creative work which will include two films and accompanying music.
The utilization of drones in various industries, such as agriculture, infrastructure inspection, and surveillance, has significantly increased in recent years. However, navigating low-altitude environments poses a challenge due to potential collisions with “unseen” obstacles like power lines and poles, leading to safety concerns and equipment damage. Traditional obstacle avoidance systems often struggle with detecting thin and transparent obstacles, making them ill-suited for scenarios involving power lines, which are essential yet difficult to perceive visually. Together with partners that are active in logistics and safety and security domains, this project proposal aims at conducting feasibility study on advanced obstacle detection and avoidance system for low-flying drones. To that end, the main research question is, “How can AI-enabled, robust and module invisible obstacle avoidance technology can be developed for low-flying drones? During this feasibility study, cutting-edge sensor technologies, such as LiDAR, radar, camera and advanced machine learning algorithms will be investigated to what extent they can be used be to accurately detect “Not easily seen” obstacles in real-time. The successful conclusion of this project will lead to a bigger project that aims to contribute to the advancement of drone safety and operational capabilities in low-altitude environments, opening new possibilities for applications in industries where low-flying drones and obstacle avoidance are critical.
Every year the police are confronted with an ever increasing number of complex cases involving missing persons. About 100 people are reported missing every year in the Netherlands, of which, an unknown number become victims of crime, and presumed buried in clandestine graves. Similarly, according to NWVA, several dead animals are also often buried illegally in clandestine graves in farm lands, which may result in the spread of diseases that have significant consequences to other animals and humans in general. Forensic investigators from both the national police (NP) and NWVA are often confronted with a dilemma: speed versus carefulness and precision. However, the current forensic investigation process of identifying and localizing clandestine graves are often labor intensive, time consuming and employ classical techniques, such as walking sticks and dogs (Police), which are not effective. Therefore, there is an urgent request from the forensic investigators to develop a new method to detect and localize clandestine graves quickly, efficiently and effectively. In this project, together with practitioners, knowledge institutes, SMEs and Field labs, practical research will be carried out to devise a new forensic investigation process to identify clandestine graves using an autonomous Crime Scene Investigative (CSI) drone. The new work process will exploit the newly adopted EU-wide drone regulation that relaxes a number of previously imposed flight restrictions. Moreover, it will effectively optimize the available drone and perception technologies in order to achieve the desired functionality, performance and operational safety in detecting/localizing clandestine graves autonomously. The proposed method will be demonstrated and validated in practical operational environments. This project will also make a demonstrable contribution to the renewal of higher professional education. The police and NVWA will be equipped with operating procedures, legislative knowledge, skills and technological expertise needed to effectively and efficiently performed their forensic investigations.
