Bioinspiration & Biomimetics最新文献

Social robots have been widely used to deliver emotional, cognitive and social support to humans. The exchange of affective gestures, instead, has been explored to a lesser extent, despite phyisical interaction with social robots could provide the same benefits as human-human interaction. Some studies that explored the touch and hugs gestures were found in literature, but there are no studies that investigate the possibility of delivering realistic caress gestures, which are, in turn, the easiest affective gestures that could be delivered with a robot. The first objective of this work was to study the kinematic and dynamic features of the caress gesture by conducting experimental acquisitions in which ten healthy volunteers were asked to caress the cheek of a mannequin in two conditions, i.e. standing and sitting. Average motion and force features were then analyzed and used to generate a realistic caress gesture with an anthropomorphic robot, with the aim of assessing the feasibility of reproducing the caress gesture with a robotic device. In addition, twenty-six healthy volunteers evaluated the anthropomorphism and perceived safety of the reproduced affective gesture by answering the Godspeed Questionnaire Series and a list of statements on the robot motion. The gesture reproduced by the robot was similar to the caress gesture performed by healthy volunteers both in terms of hand trajectory and orientation, and exchanged forces. Overall, volunteers perceived the robot motion as safe and positive emotions were elicited. The proposed approach could be adapted to humanoid robots to improve the perceived anthropomorphism and safety of the caress gesture.

Flying insects are thought to achieve energy-efficient flapping flight by storing and releasing elastic energy in their muscles, tendons, and thorax. However, "spring-wing" flight systems consisting of elastic elements coupled to nonlinear, unsteady aerodynamic forces also present possible challenges to generating stable and responsive wing motions. The energetic efficiency from resonance in insect flight is measured by the Weis-Fogh number (N), which is the ratio of peak inertial force to aerodynamic force. In this paper, we present experiments and modeling to study how resonance efficiency (which increases with N) influences the control responsiveness and perturbation resistance of flapping wingbeats. In our first experiments, we provide a step change in the input forcing amplitude to a series-elastic spring-wing system and observe the response time of the wing amplitude increase. In our second experiments we provide an external fluid flow directed at the flapping wing and study the perturbed steady-state wing motion. We evaluate both experiments across Weis-Fogh numbers from 1 < N < 10. The results indicate that spring-wing systems designed for maximum energetic efficiency also experience trade-offs in agility and stability as the Weis-Fogh number increases. Our results demonstrate that energetic efficiency and wing maneuverability are in conflict in resonant spring-wing systems suggesting that mechanical resonance presents tradeoffs in insect flight control and stability.

Animals use active sensing movements to shape the spatiotemporal characteristics of sensory signals to better perceive their environment under varying conditions. However, the underlying mechanisms governing the generation of active sensing movements are not known. To address this, we investigated the role of active sensing movements in the refuge tracking behavior ofEigenmannia virescens, a species of weakly electric fish. These fish track the longitudinal movements of a refuge in which they hide by swimming back and forth in a single linear dimension. During refuge tracking,Eigenmanniaexhibits stereotyped whole-body oscillations when the quality of the sensory signals degrades. We developed a closed-loop feedback control model to examine the role of these ancillary movements on the task performance. Our modeling suggests that fish may use active sensing to minimize predictive uncertainty in state estimation during refuge tracking. The proposed model generates simulated fish trajectories that are statistically indistinguishable from that of the actual fish, unlike the open-loop noise generator and stochastic resonance generator models in the literature. These findings reveal the significance of closed-loop control in active sensing behavior, offering new insights into the underlying mechanisms of dynamic sensory modulation.

Behaviors of animal bipedal locomotion can be described, in a simplified form, by the bipedal spring-mass model. The model provides predictive power, and helps us understand this complex dynamical behavior. In this paper, we analyzed a range of gaits generated by the bipedal spring-mass model during walking, and proposed a stabilizing touch-down condition for the swing leg. This policy is stabilizing against disturbances inside and outside the same energy level and requires only internal state information. In order to generalize the results to be independent of size and dimension of the system, we nondimensionalized the equations of motion for the bipedal spring-mass model. We presented the equilibrium gaits (a.k.a fixed point gaits) as a continuum on the walking state space showing how the different types of these gaits evolve and where they are located in the state space. Then, we showed the stability analysis of the proposed touch-down control policy for different energy levels and leg stiffness values. The results showed that the proposed touch-down control policy can stabilize towards all types of the symmetric equilibrium gaits. Moreover, we presented how the peak leg force change within an energy level and as it changes due to the type of the gait; peak force is important as a measurement of injury or damage risk on a robot or animal. Finally, we presented simulations of the bipedal spring-mass model walking on level ground and rough terrain transitioning between different equilibrium gaits as the energy level of the system changes with respect to the ground height. The analysis in this paper is theoretical, and thus applicable to further our understanding of animal bipedal locomotion and the design and control of robotic systems like ATRIAS, Cassie, and Digit.

In this paper, we present a design optimization framework for a fluidic artificial muscle (FAM) bundle subject to geometric constraints. The architecture of natural skeletal muscles allows for compact actuation packaging by distributing a substantial number of actuation elements, or muscle fiber motor units, which are to be arranged, oriented, and sized in various formations. Many researchers have drawn inspiration from these natural muscle architectures to assist in designing soft robotic systems safe for human-robot interaction. Although there are known tradeoffs identified between different muscle architectures, this optimization framework offers a method to map these architectural tradeoffs to soft actuator designs. The actuation elements selected for this study are fluidic artificial muscles (FAMs) or McKibben muscles due to their inherent compliance, cheap construction, high force-to-weight ratio, and muscle-like force-contraction behavior. Preceding studies analytically modeled the behavior of arranging FAMs in parallel, asymmetrical unipennate, and symmetrical bipennate topologies inspired by the fiber architectures found in human muscle tissues. A more recent study examined the implications of spatial constraints on bipennate FAM bundle actuation and found that by careful design, a bipennate FAM bundle can produce more force, contraction, stiffness, and work output than that of a parallel FAM bundle under equivalent spatial bounds. This multi-objective genetic algorithm-based optimization framework is used to realize desirable topological properties of a FAM bundle for maximum force and stroke for a given spatial envelope. The results help identify tradeoffs to inform design decisions based on the force and stroke demand from the desired operating task. This study further demonstrates how the desirable topological properties of the optimized FAM bundle change with different spatial bounds. .

Insects' flight is imbued with endless mysteries, offering valuable inspiration to the flapping-wing aircrafts. Particularly, the multi-mode wingbeat motion such as flapping, sweeping and twisting in coordination presents advantages in promoting unsteady aerodynamics and enhancing lift force. To achieve the flapping-twisting-sweeping motion capability, this paper proposes an at-scale three-degree-of-freedom (3-DOF) mechanism driven by three piezoelectric actuators, which consists of three four-bar mechanisms and a parallel spherical mechanism. Compliant hinges are utilized as rotating joints for power transmission. The DOF and the kinematics analysis are per-formed. The aerodynamic model of the wing and the mechanical model of the compliant hinges are considered to investigate the required driving force response of the mechanism with wing loads. By employing nonlinear programming techniques, the geometric parameters of three piezo-electric actuators are reverse-designed to match the dynamic response of the mechanism in two flapping conditions. The significance of this work lies in proposing a novel concept of an at-scale multi-degree-of-freedom wingbeat mechanism, demonstrating the feasibility of this mechanism to mimic the flexible and multi-mode wingbeat movement of insects, and providing an initial mech-anism-drive solution.

When swimming animals form cohesive groups, they can reap several benefits. Our understanding of collective animal motion has traditionally been driven by models based on phenomenological behavioral rules, but more recent work has highlighted the critical importance of hydrodynamic interactions among a group of inertial swimmers. To study how hydrodynamic interactions affect group cohesion, we develop a three-dimensional, inviscid, far-field model of a swimmer. In a group of two model swimmers, we observe several dynamical phases, including following, divergence, collision, and cohesion. Our results illustrate when cohesive groups can passively form through hydrodynamic interactions alone, and when other action is needed to maintain cohesion. We find that misalignment between swimmers makes passive cohesion less likely; nevertheless, it is possible for a cohesive group to form through passive hydrodynamic interactions alone. We also find that the geometry of swimmers critically affects the group dynamics due to its role in how swimmers sample the velocity gradient of the flow.

When designing the internals of robotic fish, variations in the internal arrangements of power and control systems cause differences in external morphological structures, particularly the positions of maximum thickness. These differences considerably affect swimming performance. This study examines the impact of the topological structure of self-propelled fish-like swimmers on hydrodynamic performance using fluid-structure interaction techniques. Fish-like swimmers with maximum thickness closest to the head exhibit optimal swimming performance, characterized by modest energy consumption for fast-response acceleration during the starting phase and higher swimming velocity for high-speed travel during steady swimming. As the maximum thickness moves toward the middle, acceleration performance significantly weakens and swimming speed decreases, although maximum energy consumption is relatively reduced. This study will provide a notable reference for the morphological design of underwater robotic fish.

The exploration of adaptive robotic systems capable of performing complex tasks in unstructured environments, such as underwater salvage operations, presents a significant challenge. Traditional rigid grippers often struggle with adaptability, whereas bioinspired soft grippers offer enhanced flexibility and adaptability to varied object shapes. In this study, we present a novel bioinspired soft robotic gripper integrated with a shape memory alloy (SMA) actuated suction cup, inspired by the versatile grasping strategies of octopus arms and suckers. Our design leverages a tendon-driven composite arm, enabling precise bending and adaptive grasping, combined with SMA technology to create a compact, efficient suction mechanism. We develop comprehensive kinematic and static models to predict the interaction between arm bending deflection and suction force, thereby optimizing the gripper's performance. Experimental validation demonstrates the efficacy of our integrated design, highlighting its potential for advanced manipulation tasks in challenging environments. This work provides a new perspective on the integration of bioinspired design principles with smart materials, paving the way for future innovations in adaptive robotic systems. .

Recently, vision-based unmanned aerial vehicle (UAV) swarming has emerged as a promising alternative that can overcome the adaptability and scalability limitations of distributed and communication-based UAV swarm systems. While most vision-based control algorithms are predicated on the detection of neighboring objects, they often overlook key perceptual factors such as visual occlusion and the impact of visual sensor limitations on swarm performance. To address the interaction problem of neighbor selection at the core of self-organizing UAV swarm control, a perceptually realistic finite perception visual (FPV) neighbor selection model is proposed, which is based on the lateral visual characteristics of birds, incorporates adjustable lateral visual field widths and orientations, and is able to ignore occluded agents. Based on the FPV model, a neighbor selection method based on the acute angle test (AAT) is proposed, which overcomes the limitation that the traditional neighbor selection mechanism can only interact with the nearest neighboring agents. A large number of Monte Carlo simulation comparison experiments show that the proposed FPV+AAT neighbor selection mechanism can reduce the redundant communication burden between large-scale self-organized UAV swarms, and outperforms the traditional neighbor selection method in terms of order, safety, union, connectivity, and noise resistance.