353 research outputs found

    In-channel experiments on vertical swimming with bacteria-like robots

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    Bio-inspired micro-robots are of great importance as to implement versatile microsystems for a variety of in vivo and in vitro applications in medicine and biology. Accurate models are necessary to understand the swimming and rigidbody dynamics of such systems. In this study, a series of experiments are conducted with a two-link cm-scale bioinspired robot moving vertically without a tether, in siliconefilled narrow cylindrical glass channels. Swimming velocities are obtained for a set of varying tail and wave geometries, and employed to validate a resistive force theory (RFT) model using modified resistance coefficients based on measured forward velocity and body rotation rates

    Central Pattern Generator In Bio-Inspired Robot: Simulation Using MATLAB

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    Central pattern generator (CPG) is defined here as a neural network responsible for the production of the timing cues of a rhythmic motor output pattern. In biological system, the CPG is a network of neurons that generate the rhythmic movements such as locomotion of animals

    Emergent adaptive behaviour of GRN-controlled simulated robots in a changing environment

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    We developed a bio-inspired robot controller combining an artificial genome with an agent-based control system. The genome encodes a gene regulatory network (GRN) that is switched on by environmental cues and, following the rules of transcriptional regulation, provides output signals to actuators. Whereas the genome represents the full encoding of the transcriptional network, the agent-based system mimics the active regulatory network and signal transduction system also present in naturally occurring biological systems. Using such a design that separates the static from the conditionally active part of the gene regulatory network contributes to a better general adaptive behaviour. Here, we have explored the potential of our platform with respect to the evolution of adaptive behaviour, such as preying when food becomes scarce, in a complex and changing environment and show through simulations of swarm robots in an A-life environment that evolution of collective behaviour likely can be attributed to bio-inspired evolutionary processes acting at different levels, from the gene and the genome to the individual robot and robot population

    Spatial Representation and Navigation in a Bio-inspired Robot

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    A biologically inspired computational model of rodent repre-sentation?based (locale) navigation is presented. The model combines visual input in the form of realistic two dimensional grey-scale images and odometer signals to drive the firing of simulated place and head direction cells via Hebbian synapses. The space representation is built incrementally and on-line without any prior information about the environment and consists of a large population of location-sensitive units (place cells) with overlapping receptive fields. Goal navigation is performed using reinforcement learning in continuous state and action spaces, where the state space is represented by population activity of the place cells. The model is able to reproduce a number of behavioral and neuro-physiological data on rodents. Performance of the model was tested on both simulated and real mobile Khepera robots in a set of behavioral tasks and is comparable to the performance of animals in similar tasks

    Integrating Reconfigurable Foot Design, Multi-modal Contact Sensing, and Terrain Classification for Bipedal Locomotion

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    The ability of bipedal robots to adapt to diverse and unstructured terrain conditions is crucial for their deployment in real-world environments. To this end, we present a novel, bio-inspired robot foot design with stabilizing tarsal segments and a multifarious sensor suite involving acoustic, capacitive, tactile, temperature, and acceleration sensors. A real-time signal processing and terrain classification system is developed and evaluated. The sensed terrain information is used to control actuated segments of the foot, leading to improved ground contact and stability. The proposed framework highlights the potential of the sensor-integrated adaptive foot for intelligent and adaptive locomotion.Comment: 7 pages, 6 figure

    Describing Robotic Bat Flight with Stable Periodic Orbits

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    From a dynamic system point of view, bat locomotion stands out among other forms of flight. During a large part of bat wingbeat cycle the moving body is not in a static equilibrium. This is in sharp contrast to what we observe in other simpler forms of flight such as insects, which stay at their static equilibrium. Encouraged by biological examinations that have revealed bats exhibit periodic and stable limit cycles, this work demonstrates that one effective approach to stabilize articulated flying robots with bat morphology is locating feasible limit cycles for these robots; then, designing controllers that retain the closed-loop system trajectories within a bounded neighborhood of the designed periodic orbits. This control design paradigm has been evaluated in practice on a recently developed bio-inspired robot called Bat Bot (B2)

    Closed-Loop Perching and Spatial Guidance Laws for Bio-Inspired Articulated Wing MAV

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    This paper presents the underlying theoretical developments and successful experimental demonstrations of perching of an aerial robot. The open-loop lateral-directional dynamics of the robot are inherently unstable because it lacks a vertical tail for agility, similar to birds. A unique feature of this robot is that it uses wing articulation for controlling the flight path angle as well as the heading. New guidance algorithms with guaranteed stability are obtained by rewriting the flight dynamic equations in the spatial domain rather than as functions of time, after which dynamic inversion is employed. It is shown that nonlinear dynamic inversion naturally leads to proportional-integral-derivative (PID) controllers, thereby providing an exact method for tuning the gains. The effectiveness of the proposed bio-inspired robot design and its novel closed-loop perching controller has been successfully demonstrated with perched landings on a human hand
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