Periodic Reporting for period 3 - I-Seed (Towards new frontiers for distributed environmental monitoring based on an ecosystem of plant seed-like soft robots)
Reporting period: 2024-01-01 to 2024-12-31
The EU FET Proactive Environmental Intelligence project “I-Seed” targeted towards the development of a radically simplified and environmentally friendly approach for monitoring topsoil and air. Specifically, I-Seed aimed at developing a new generation of self-deployable and biodegradable soft miniaturized robots, inspired by the morphology and dispersion abilities of plant seeds, able to perform a low-cost, environmentally responsible, and in-situ detection.
The natural functional mechanisms of seeds dispersal offer a rich source of robust, highly adaptive, mass and energy efficient mechanisms, which can be selected and implemented for advanced, but simple, technological inventions. I-Seed robots are conceived as unique in their movement abilities because inspired by passive mechanisms and materials of natural seeds, as well as in their environmentally friendly design because made of biodegradable components. Sensing is based on a chemical transduction mechanism in a stimulus-responsive sensor material with fluorescence-based optical readout, which can be read via one or more drones equipped with fluorescent LiDAR technology and a software able to perform a real time georeferencing of data.
Tested in laboratory conditions and in controlled outdoor scenario, the project demonstrated the feasibility of the use of the I-Seed robotic ecosystem for collecting environmental data in-situ.
The collection of environmental data and their analysis target the filling of geographical gaps to improve ongoing monitoring networks in areas where no monitoring infrastructures are available with low investment and management costs.
The natural functional mechanisms of seeds dispersal offer a rich source of robust, highly adaptive, mass and energy efficient mechanisms, which can be selected and implemented for advanced, but simple, technological inventions. I-Seed robots are conceived as unique in their movement abilities because inspired by passive mechanisms and materials of natural seeds, as well as in their environmentally friendly design because made of biodegradable components. Sensing is based on a chemical transduction mechanism in a stimulus-responsive sensor material with fluorescence-based optical readout, which can be read via one or more drones equipped with fluorescent LiDAR technology and a software able to perform a real time georeferencing of data.
Tested in laboratory conditions and in controlled outdoor scenario, the project demonstrated the feasibility of the use of the I-Seed robotic ecosystem for collecting environmental data in-situ.
The collection of environmental data and their analysis target the filling of geographical gaps to improve ongoing monitoring networks in areas where no monitoring infrastructures are available with low investment and management costs.
The project started with the definition of the I-Seed environmental scenarios and field validation strategy, followed by a series of scientific and technical activities for the design and development of the I-Seed platform. Specifically, a focused study of plant seed materials and biomechanics was carried out in order to define useful specifications for the modelling and the design of the artificial systems in terms of multi-functional materials, their structural properties, and morphological adaptation. In parallel, we carried out activities for the mathematical modelling of movements of natural and artificial seeds, for the design and development of the artificial seeds body and their sensing material, for the development of the active laser-induced fluorescence system on the drone, as well as for the geo-referencing software and smart flight controller.
During the initial three years of the project (2021-2023), we successfully developed five types of seed-inspired robots, four fluorescent sensors (for detecting mercury, CO2, humidity, and temperature) and a drone/LIDAR system. In June 2024, we conducted the first in-field integration tests of the robots and fluorescent temperature sensor in Wageningen (Netherlands) with the fluorescence signal measured by the drone/LIDAR system. By the end of 2024, we have assessed the potentiality of the environmental measurements achievable with the I-Seed ecosystem, comparing them with conventional technologies.
The project successfully fostered cross-disciplinary collaboration between the biorobotics and environmental science communities, as well as citizen-focused eco-innovation initiatives. It led to the publication of 16 journal articles—three of which featured on the cover—alongside three conference papers, over 80 presentations at scientific events, and one patent. The consortium organized special sessions, workshops, scientific cafés, a forum, the first PhD school on Environmental Intelligence, and actively participated in exhibitions at robotics conferences and science festivals. The project gained widespread media attention with over 140 mentions in national and international outlets. Key deliverables included a white paper with an associated journal publication, four Blueprint documents on Environmental Intelligence—culminating in an EIC recommendation report. A comprehensive exploitation plans featuring market analysis was released.
During the initial three years of the project (2021-2023), we successfully developed five types of seed-inspired robots, four fluorescent sensors (for detecting mercury, CO2, humidity, and temperature) and a drone/LIDAR system. In June 2024, we conducted the first in-field integration tests of the robots and fluorescent temperature sensor in Wageningen (Netherlands) with the fluorescence signal measured by the drone/LIDAR system. By the end of 2024, we have assessed the potentiality of the environmental measurements achievable with the I-Seed ecosystem, comparing them with conventional technologies.
The project successfully fostered cross-disciplinary collaboration between the biorobotics and environmental science communities, as well as citizen-focused eco-innovation initiatives. It led to the publication of 16 journal articles—three of which featured on the cover—alongside three conference papers, over 80 presentations at scientific events, and one patent. The consortium organized special sessions, workshops, scientific cafés, a forum, the first PhD school on Environmental Intelligence, and actively participated in exhibitions at robotics conferences and science festivals. The project gained widespread media attention with over 140 mentions in national and international outlets. Key deliverables included a white paper with an associated journal publication, four Blueprint documents on Environmental Intelligence—culminating in an EIC recommendation report. A comprehensive exploitation plans featuring market analysis was released.
One of the first challenges was defining a methodology to translate the biological principles of selected plant seeds and their dispersal strategies into the design and fabrication of environmentally responsive, seed-like soft robots made from multifunctional biodegradable materials.
For the I-Seed objective of measuring conditions in both air above soil and topsoil, two groups of natural seeds were identified and analyzed: (1) self-burying seeds that passively explore and penetrate soil fractures using a hygroscopic seed awn that responds to humidity changes; (2) flying seeds that rely on morphology and structure to disperse over long distances via wind.
Building on these principles, the next challenge was to create artificial seed-like robots from biodegradable materials that provide structural support and respond dynamically to environmental stimuli. Movement and dispersion are achieved through material computation, enabling passive mobility without internal energy by exploiting morphology, structure, and biomechanics/aerodynamics.
Mechanical modeling of biological and robotic seeds helped formulate reduced fluid-structure interaction models to optimize shape and elasticity for flight style, trajectory control, and performance, as well as soil interaction and energetics.
Sensing in artificial seeds was developed using transduction-based sensor materials that react to environmental factors like temperature, humidity, or chemicals by changing optical properties. Signal reading relied on optical and fluorescence detection through a multi-wavelength fluorescence LiDAR system capable of simultaneous excitation detection, extending laser-induced fluorescence methods used in vegetation to other I-Seed materials.
LiDAR data post-processing and drone flight control required designing a “smart” flight controller with deep learning software for real-time data processing and desktop post-processing.
The conceived I-Seed scenario aimed to increase spatial resolution in monitoring contaminated sites by developing low-cost technology for continuous field campaigns, enabling verification of ecosystem remediation efforts.
Beyond scientific and technical advances, I-Seed united bio-roboticists and environmental scientists, laying the foundation for a cross-disciplinary community of “ecoroboticists” and environmental intelligence researchers. Through events and training, it supported the growth of a new generation of experts developing sustainable technologies to address urgent environmental challenges.
For the I-Seed objective of measuring conditions in both air above soil and topsoil, two groups of natural seeds were identified and analyzed: (1) self-burying seeds that passively explore and penetrate soil fractures using a hygroscopic seed awn that responds to humidity changes; (2) flying seeds that rely on morphology and structure to disperse over long distances via wind.
Building on these principles, the next challenge was to create artificial seed-like robots from biodegradable materials that provide structural support and respond dynamically to environmental stimuli. Movement and dispersion are achieved through material computation, enabling passive mobility without internal energy by exploiting morphology, structure, and biomechanics/aerodynamics.
Mechanical modeling of biological and robotic seeds helped formulate reduced fluid-structure interaction models to optimize shape and elasticity for flight style, trajectory control, and performance, as well as soil interaction and energetics.
Sensing in artificial seeds was developed using transduction-based sensor materials that react to environmental factors like temperature, humidity, or chemicals by changing optical properties. Signal reading relied on optical and fluorescence detection through a multi-wavelength fluorescence LiDAR system capable of simultaneous excitation detection, extending laser-induced fluorescence methods used in vegetation to other I-Seed materials.
LiDAR data post-processing and drone flight control required designing a “smart” flight controller with deep learning software for real-time data processing and desktop post-processing.
The conceived I-Seed scenario aimed to increase spatial resolution in monitoring contaminated sites by developing low-cost technology for continuous field campaigns, enabling verification of ecosystem remediation efforts.
Beyond scientific and technical advances, I-Seed united bio-roboticists and environmental scientists, laying the foundation for a cross-disciplinary community of “ecoroboticists” and environmental intelligence researchers. Through events and training, it supported the growth of a new generation of experts developing sustainable technologies to address urgent environmental challenges.