7,676 research outputs found
Calibration method to improve transfer from simulation to quadruped robots
Using passive compliance in robotic locomotion has been seen as a cheap and straightforward way of increasing the performance in energy consumption and robustness. However, the control for such systems remains quite challenging when using traditional robotic techniques. The progress in machine learning opens a horizon of new possibilities in this direction but the training methods are generally too long and laborious to be conducted on a real robot platform. On the other hand, learning a control policy in simulation also raises a lot of complication in the transfer. In this paper, we designed a cheap quadruped robot and detail a calibration method to optimize a simulation model in order to facilitate the transfer of parametric motor primitives. We present results validating the transfer of Central Pattern Generators (CPG) learned in simulation to the robot which already give positive insights on the validity of this method
Neurobiologically Inspired Control of Engineered Flapping Flight
This article presents a new control approach for engineered
flapping flight with many interacting degrees of freedom. This paper explores the applications of neurobiologically
inspired control systems in the form of Central Pattern Generators (CPG) to generate wing trajectories for potential flapping flight MAVs. We present a rigorous mathematical and control theoretic framework to design complex three dimensional motions of flapping wings. Most
flapping flight demonstrators are mechanically limited in generating the wing trajectories. Because CPGs lend themselves to more biological examples of flight, a novel
robotic model has been developed to emulate the flight of bats. This model has shoulder and leg joints totaling 10 degrees of freedom for control of wing properties. Results of wind tunnel experiments and numerical simulation of CPG-based flight control validate the effectiveness of the proposed neurobiologically inspired control approach
Design of flexible actuators using electro-active polymers and CPG-based control strategies
Biomimetic design based on inspiration from nature for solutions for engineering problems
has been practiced throughout human history. Invertebrate animals without a skeletal struc-ture have
exible, robust and agile movements. For example, the octopus arm which is able
to grip objects by exerting large forces, moves with a wide range of velocities, and manip-ulates delicate objects, without any rigid skeletal elements. Two key applications of such
biomimetic systems are compliant and lightweight robotic arms for tightly constrained spaces
and energy-e cient muscle actuators for biomimetic locomotion.
Inspired by octopus arm, in this thesis we investiagte di erent design concepts and require-ments for using dielectric electroactive polymers (EAP) for designing of
exible actuators
and manipulators. A model-guided approach to design a bio-inspired
exible actuator mod-ule is presented analyzed. Further, mathematical modelling for Central Pattern Generators
(CPGs) is presented. The condition for phase synchronization of coupled single chain oscil-lators is derived and various techniques for pattern generation using oscillator network are
studied. Finally, octopus based control using Central Pattern Generators (CPGs) is brie
y
discussed
Neuro-mechanical entrainment in a bipedal robotic walking platform
In this study, we investigated the use of van der Pol oscillators in a 4-dof embodied bipedal robotic platform for the purposes of planar walking. The oscillator controlled the hip and knee joints of the robot and was capable of generating waveforms with the correct frequency and phase so as to entrain with the mechanical system. Lowering its oscillation frequency resulted in an increase to the walking pace, indicating exploitation of the global natural dynamics. This is verified by its operation in absence of entrainment, where faster limb motion results in a slower overall walking pace
A SpiNNaker Application: Design, Implementation and Validation of SCPGs
In this paper, we present the numerical results of the implementation
of a Spiking Central Pattern Generator (SCPG) on a SpiNNaker
board. The SCPG is a network of current-based leaky integrateand-
fire (LIF) neurons, which generates periodic spike trains that correspond
to different locomotion gaits (i.e. walk, trot, run). To generate
such patterns, the SCPG has been configured with different topologies,
and its parameters have been experimentally estimated. To validate our
designs, we have implemented them on the SpiNNaker board using PyNN
and we have embedded it on a hexapod robot. The system includes a
Dynamic Vision Sensor system able to command a pattern to the robot
depending on the frequency of the events fired. The more activity the
DVS produces, the faster that the pattern that is commanded will be.Ministerio de Economía y Competitividad TEC2016-77785-
Neuro-mechanical entrainment in a bipedal robotic walking platform
In this study, we investigated the use of van der Pol oscillators in a 4-dof embodied bipedal robotic platform for the purposes of planar walking. The oscillator controlled the hip and knee joints of the robot and was capable of generating waveforms with the correct frequency and phase so as to entrain with the mechanical system. Lowering its oscillation frequency resulted in an increase to the walking pace, indicating exploitation of the global natural dynamics. This is verified by its operation in absence of entrainment, where faster limb motion results in a slower overall walking pace
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