Towards new frontiers for distributed environmental monitoring based on an ecosystem of plant seed-like soft robots

Mazzolai, Barbara; Kraus, Tobias; Pirrone, Nicola; Kooistra, L.; Simone, Antonio De; Cottin, Antoine; Margheri, Laura

doi:10.1145/3462203.3475915

Cited by 10 publications

(6 citation statements)

References 6 publications

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“…Consistently, adopting terrestrial and aerial robotic solutions, we could gather data for seed plantation toward reforestation against desertification to capture carbon dioxide, or to feed population and local economies, and to evaluate new pathogens and vector-borne diseases (SDG-3, 8, and 13) (Wade et al, 2018;Chowdhary et al, 2019;Zhou et al, 2022). C2C self-burial systems or climbing micro-soft robots could be adopted on crops to gather targeted genetic information and provide precise monitoring and surveillance of plants and soil (SDG-8, 12, and 15) (Fiorello et al, 2021;Horton et al, 2021;Mazzolai et al, 2021). Furthermore, C2C micro-robots can be released in water sources and infrastructures to detect pollutants and/or nutrients (SDG-6).…”

Section: Robots With Distributed Sensors For Monitoring and Remediationmentioning

confidence: 99%

Soft robotics towards sustainable development goals and climate actions

2023

Self Cite

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Soft robotics technology can aid in achieving United Nations’ Sustainable Development Goals (SDGs) and the Paris Climate Agreement through development of autonomous, environmentally responsible machines powered by renewable energy. By utilizing soft robotics, we can mitigate the detrimental effects of climate change on human society and the natural world through fostering adaptation, restoration, and remediation. Moreover, the implementation of soft robotics can lead to groundbreaking discoveries in material science, biology, control systems, energy efficiency, and sustainable manufacturing processes. However, to achieve these goals, we need further improvements in understanding biological principles at the basis of embodied and physical intelligence, environment-friendly materials, and energy-saving strategies to design and manufacture self-piloting and field-ready soft robots. This paper provides insights on how soft robotics can address the pressing issue of environmental sustainability. Sustainable manufacturing of soft robots at a large scale, exploring the potential of biodegradable and bioinspired materials, and integrating onboard renewable energy sources to promote autonomy and intelligence are some of the urgent challenges of this field that we discuss in this paper. Specifically, we will present field-ready soft robots that address targeted productive applications in urban farming, healthcare, land and ocean preservation, disaster remediation, and clean and affordable energy, thus supporting some of the SDGs. By embracing soft robotics as a solution, we can concretely support economic growth and sustainable industry, drive solutions for environment protection and clean energy, and improve overall health and well-being.

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Section: Robots With Distributed Sensors For Monitoring and Remediationmentioning

confidence: 99%

Soft robotics towards sustainable development goals and climate actions

2023

Self Cite

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“…Some promising work has been done towards fully biodegradable sensors and robots [11], [12] with fully biodegradable components for batteries [13]- [15], actuators [16], or structural components [17]- [19]. Since the electronics needed for recording and transmitting data are most difficult to replicate with biodegradable materials, another approach is to develop sensors with active materials that react to changing environmental parameters with changes in shape or optical properties that can be sensed remotely [20] or remote reading of biodegradable sensors with passive RFID antennas [21]. However, these approaches are still in the research and development stage, and not readily deployable in the field.…”

Section: Introductionmentioning

confidence: 99%

Biodegradable Origami Gripper Actuated with Gelatin Hydrogel for Aerial Sensor Attachment to Tree Branches

Geckeler,

Pizzani,

Mintchev

2023

2023 IEEE International Conference on Robotics and Automation (ICRA)

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“…Soft robots have a wide range of applications, including medical and surgical devices [26][27][28], industrial automation [29][30][31][32][33], human-robot interaction [34][35][36][37][38], environmental monitoring and underwater exploration [39,40], biomimicry [41][42][43][44][45][46][47][48], search and rescue operations [49] and entertainment [50,51].…”

Section: Introductionmentioning

confidence: 99%

Intermediate Encoding Layers for the Generative Design of 2D Soft Robot Actuators: A Comparison of CPPN’s, L-Systems and Random Generation

Venter

Conradie

2023

MCA

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This paper introduced a comparison method for three explicitly defined intermediate encoding methods in generative design for two-dimensional soft robotic units. This study evaluates a conventional genetic algorithm with full access to removing elements from the design domain using an implicit random encoding layer, a Lindenmayer system encoding mimicking biological growth patterns and a compositional pattern producing network encoding for 2D pattern generation. The objective of the optimisation problem is to match the deformation of a single actuator unit with a desired target shape, specifically uni-axial elongation, under internal pressure. The study results suggest that the Lindenmayer system encoding generates candidate units with fewer function evaluations than the traditional implicitly encoded genetic algorithm. However, the distribution of constraint and internal energy is similar to that of the random encoding, and the Lindenmayer system encoding produces a less diverse population of candidate units. In contrast, despite requiring more function evaluations than the Lindenmayer System encoding, the Compositional Pattern Producing Network encoding produces a similar diversity of candidate units. Overall, the Compositional Pattern Producing Network encoding results in a proportionally higher number of high-performing units than the random or Lindenmayer system encoding, making it a viable alternative to a conventional monolithic approach. The results suggest that the compositional pattern producing network encoding may be a promising approach for designing soft robotic actuators with desirable performance characteristics.

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Towards new frontiers for distributed environmental monitoring based on an ecosystem of plant seed-like soft robots

Cited by 10 publications

References 6 publications

Soft robotics towards sustainable development goals and climate actions

Soft robotics towards sustainable development goals and climate actions

Biodegradable Origami Gripper Actuated with Gelatin Hydrogel for Aerial Sensor Attachment to Tree Branches

Intermediate Encoding Layers for the Generative Design of 2D Soft Robot Actuators: A Comparison of CPPN’s, L-Systems and Random Generation

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