258 research outputs found
Robot-Locust Social Information Transfer Occurs in Predator Avoidance Contexts
Social learning is an evolutionarily important ability increasingly attributed also to invertebrate species. Interfacing robots with animals represents a promising strategy to investigate social learning. Herein, we studied if the gregarious form of Locusta migratoria, a particularly suited model to examine social learning, can use social information provided by robotic demonstrators to optimize their predator avoidance. Robotic demonstrators with different silhouettes and colours (biomimetic or neutral) were used to investigate if their rotation on a rod (e.g. hiding behaviour) elicited the same behaviour in neighbouring locusts. Locusts’ responses were affected by different robotic demonstrators, observing a significant impact of the biomimetic silhouette in reducing the latency duration, and in promoting social learning (e.g. locusts displaying hiding behaviour after observing it in robotic demonstrators). A significant impact of colour patterns in triggering socially induced hiding behaviour was also recorded, especially when the biomimetic silhouette was coloured with the gregarious-like pattern. This research indicates gregarious locusts exploit social information in specific ecological contexts, providing basic knowledge on the complex behavioural ecology and social biology in invertebrates. The proposed animal-robot interaction paradigm shows the role of robots as carrier of social information to living organisms, suggesting social biorobotics as advanced and sustainable approach for socio-biology investigation, and environmental management
How aggressive interactions with biomimetic agents optimize reproductive performances in mass-reared males of the Mediterranean fruit fly
Mass-rearing procedures of insect species, often used in biological control and Sterile Insect Technique, can reduce the insects competitiveness in foraging, dispersal, and mating. The evocation of certain behaviours responsible to induce specific neuroendocrine products may restore or improve the competitiveness of mass-reared individuals. Herein, we used a mass-reared strain of Ceratitis capitata as model organism. C. capitata is a polyphagous pest exhibiting territorial displays that are closely related to its reproductive performance. We tested if the behaviour of C. capitata males could be altered by hybrid aggressive interactions with a conspecific-mimicking robotic fly, leading to more competitive individuals in subsequent mating events. Aggressive interactions with the robotic fly had a notable effect on subsequent courtship and mating sequences of males that performed longer courtship displays compared to naĂŻve individuals. Furthermore, previous interactions with the robotic fly produced a higher mating success of males. Reproductive performances of C. capitata males may be improved by specific octopaminergic neurones activated during previous aggressive interactions with the robotic fly. This study adds fundamental knowledge on the potential role of specific neuro-behavioural processes in the ecology of tephritid species and paves the way to innovative biotechnological control methods based on robotics and bionics
Assessing black soldier fly pupation and survival in lunar regolith simulant: Implications for sustainable controlled habitats on the Moon
Bioregenerative life-support systems (BLSSs) will be crucial for extended space missions and extraterrestrial
habitats. The black soldier fly, Hermetia illucens, is recognized for its efficient organic waste consumption, making
it well-suited for closed environments like spacecraft. Our study assessed H. illucens adaptability to different substrates,
including a lunar regolith simulant, pertinent to future lunar colonization. Remarkably resilient, H. illucens
prepupal larvae successfully pupated in all tested substrates, but pupation timing varied, with no-substrate
larvae pupating later. Pupal stage duration also differed, particularly with lunar regolith simulant and sand treatments
resulting in longer durations. Substrate treatments significantly influenced the number of emerged adults,
with lunar regolith simulant yielding more adults than the no-substrate treatment. Additionally, sand and wood
shavings treatments produced more adults, highlighting H. illucens adaptability to various substrates, including
lunar regolith. These findings are crucial for future BLSSs design. Additionally, H. illucens adaptability to lunar
regolith provides insights into life's adaptability in space environments, guiding future experiments on celestial
bodies. This study provides critical data on how different substrates, including lunar regolith simulants, influence
H. illucens development and survival, advancing BLSSs and ecological science in both space and terrestrial contexts
Underactuated Robotic Fish Control: Maneuverability and Adaptability Through Proprioceptive Feedback
Bioinspired robotics is a promising technology for minimizing environmental disruption during underwater inspection, exploration, and monitoring. In this research, we propose a control strategy for an underactuated robotic fish that mimics the oscillatory movement of a real fish’s tail using only one DC motor. Our control strategy is bioinspired to Central Pattern Generators (CPGs) and integrates proprioceptive sensory feedback. Specifically, we introduced the angular position of the tail as an input control variable to integrate a feedback into CPG circuits. This makes the controller adaptive to changes in the tail structure, weight, or the environment in which the robotic fish swims, allowing it to change its swimming speed and steering performance. Our robotic fish can swim at a speed between 0.18 and 0.26 body lengths per second (BL/s), with a tail beating frequency between 1.7 and 2.3 Hz. It can also vary its steering angular speed in the range of 0.08 rad/s, with a relative change in the curvature radius of 0.25 m. With modifications to the modular design, we can further improve the speed and steering performance while maintaining the developed control strategy. This research highlights the potential of bioinspired robotics to address pressing environmental challenges while improving solutions efficiency, reliability and reducing development costs
A Novel and Accurate BiLSTM Configuration Controller for Modular Soft Robots with Module Number Adaptability
Modular soft robots have shown higher potential in sophisticated tasks than
single-module robots. However, the modular structure incurs the complexity of
accurate control and necessitates a control strategy specifically for modular
robots. In this paper, we introduce a data collection strategy and a novel and
accurate bidirectional LSTM configuration controller for modular soft robots
with module number adaptability. Such a controller can control module
configurations in robots with different module numbers. Simulation cable-driven
robots and real pneumatic robots have been included in experiments to validate
the proposed approaches, and we have proven that our controller can be
leveraged even with the increase or decrease of module number. This is the
first paper that gets inspiration from the physical structure of modular robots
and utilizes bidirectional LSTM for module number adaptability. Future work may
include a planning method that bridges the task and configuration spaces and
the integration of an online controller.Comment: 10 figures, 4 table
A Hybrid Adaptive Controller for Soft Robot Interchangeability
Soft robots have been leveraged in considerable areas like surgery,
rehabilitation, and bionics due to their softness, flexibility, and safety.
However, it is challenging to produce two same soft robots even with the same
mold and manufacturing process owing to the complexity of soft materials.
Meanwhile, widespread usage of a system requires the ability to fabricate
replaceable components, which is interchangeability. Due to the necessity of
this property, a hybrid adaptive controller is introduced to achieve
interchangeability from the perspective of control approaches. This method
utilizes an offline trained recurrent neural network controller to cope with
the nonlinear and delayed response from soft robots. Furthermore, an online
optimizing kinematics controller is applied to decrease the error caused by the
above neural network controller. Soft pneumatic robots with different
deformation properties but the same mold have been included for validation
experiments. In the experiments, the systems with different actuation
configurations and the different robots follow the desired trajectory with
errors of 0.040 and 0.030 compared with the working space length, respectively.
Such an adaptive controller also shows good performance on different control
frequencies and desired velocities. This controller endows soft robots with the
potential for wide application, and future work may include different offline
and online controllers. A weight parameter adjusting strategy may also be
proposed in the future.Comment: 8 pages, 9 figures, 4 table
Multiple cues produced by a robotic fish modulate aggressive behaviour in Siamese fighting fishes
The use of robotics to establish social interactions between animals and robots, represents an elegant and innovative method to investigate animal behaviour. However, robots are still underused to investigate high complex and flexible behaviours, such as aggression. Here, Betta splendens was tested as model system to shed light on the effect of a robotic fish eliciting aggression. We evaluated how multiple signal systems, including a light stimulus, affect aggressive responses in B. splendens. Furthermore, we conducted experiments to estimate if aggressive responses were triggered by the biomimetic shape of fish replica, or whether any intruder object was effective as well. Male fishes showed longer and higher aggressive displays as puzzled stimuli from the fish replica increased. When the fish replica emitted its full sequence of cues, the intensity of aggression exceeded even that produced by real fish opponents. Fish replica shape was necessary for conspecific opponent perception, evoking significant aggressive responses. Overall, this study highlights that the efficacy of an artificial opponent eliciting aggressive behaviour in fish can be boosted by exposure to multiple signals. Optimizing the cue combination delivered by the robotic fish replica may be helpful to predict escalating levels of aggression
A Bioinspired Control Strategy Ensures Maneuverability and Adaptability for Dynamic Environments in an Underactuated Robotic Fish
Bioinspired underwater robots can move efficiently, with agility, even in complex aquatic areas, reducing marine ecosystem
disturbance during exploration and inspection. These robots can improve animal farming conditions and preserve wildlife.
This study proposes a muscle-like control for an underactuated robot in carangiform swimming mode. The artifact exploits
a single DC motor with a non-blocking transmission system to convert the motor’s oscillatory motion into the fishtail’s
oscillation. The transmission system combines a magnetic coupling and a wire-driven mechanism. The control strategy was
inspired by central pattern generators (CPGs) to control the torque exerted on the fishtail. It integrates proprioceptive sensory
feedback to investigate the adaptability to different contexts. A parametrized control law relates the reference target to the
fishtail’s angular position. Several tests were carried out to validate the control strategy. The proprioceptive feedback revealed
that the controller can adapt to different environments and tail structure changes. The control lawparameters variation accesses
the robotic fish’s multi-modal swimming. Our solution can vary the swimming speed of 0.08 body lengths per second (BL/s),
and change the steering direction and performance by an angular speed and turning curvature radius of 0.08 rad/s and 0.25
m, respectively. Performance can be improved with design changes, while still maintaining the developed control strategy.
This approach ensures the robot’s maneuverability despite its underactuated structure. Energy consumption was evaluated
under the robotic platform’s control and design. Our bioinspired control system offers an effective, reliable, and sustainable
solution for exploring and monitoring aquatic environments, while minimizing human risks and preserving the ecosystem.
Additionally, it creates new and innovative opportunities for interacting with marine species. Our findings demonstrate the
potential of bioinspired technologies to advance the field of marine science and conservation
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