148 research outputs found
Multiple chaotic central pattern generators with learning for legged locomotion and malfunction compensation
An originally chaotic system can be controlled into various periodic
dynamics. When it is implemented into a legged robot's locomotion control as a
central pattern generator (CPG), sophisticated gait patterns arise so that the
robot can perform various walking behaviors. However, such a single chaotic CPG
controller has difficulties dealing with leg malfunction. Specifically, in the
scenarios presented here, its movement permanently deviates from the desired
trajectory. To address this problem, we extend the single chaotic CPG to
multiple CPGs with learning. The learning mechanism is based on a simulated
annealing algorithm. In a normal situation, the CPGs synchronize and their
dynamics are identical. With leg malfunction or disability, the CPGs lose
synchronization leading to independent dynamics. In this case, the learning
mechanism is applied to automatically adjust the remaining legs' oscillation
frequencies so that the robot adapts its locomotion to deal with the
malfunction. As a consequence, the trajectory produced by the multiple chaotic
CPGs resembles the original trajectory far better than the one produced by only
a single CPG. The performance of the system is evaluated first in a physical
simulation of a quadruped as well as a hexapod robot and finally in a real
six-legged walking machine called AMOSII. The experimental results presented
here reveal that using multiple CPGs with learning is an effective approach for
adaptive locomotion generation where, for instance, different body parts have
to perform independent movements for malfunction compensation.Comment: 48 pages, 16 figures, Information Sciences 201
An Overview of Legged Robots
The objective of this paper is to present the evolution and the state-of-theart in the area of legged locomotion systems. In a first phase different possibilities for mobile robots are discussed, namely the case of artificial legged locomotion systems, while emphasizing their advantages and limitations. In a second phase an historical overview of the evolution of these systems is presented, bearing in mind several particular cases often considered as milestones on the technological and scientific progress. After this historical timeline, some of the present day systems are examined and their performance is analyzed. In a third phase are pointed out the major areas for research and development that are presently being followed in the construction of legged robots. Finally, some of the problems still unsolved, that remain defying robotics research, are also addressed.N/
A hexapod walker using a heterarchical architecture for action selection
Schilling M, Paskarbeit J, Hoinville T, et al. A hexapod walker using a heterarchical architecture for action selection. Frontiers in Computational Neuroscience. 2013;7:126.Moving in a cluttered environment with a six-legged walking machine that has additional body actuators, therefore controlling 22 DoFs, is not a trivial task. Already simple forward walking on a flat plane requires the system to select between different internal states. The orchestration of these states depends on walking velocity and on external disturbances. Such disturbances occur continuously, for example due to irregular up-and-down movements of the body or slipping of the legs, even on flat surfaces, in particular when negotiating tight curves. The number of possible states is further increased when the system is allowed to walk backward or when front legs are used as grippers and cannot contribute to walking. Further states are necessary for expansion that allow for navigation. Here we demonstrate a solution for the selection and sequencing of different (attractor) states required to control different behaviors as are forward walking at different speeds, backward walking, as well as negotiation of tight curves. This selection is made by a recurrent neural network (RNN) of motivation units, controlling a bank of decentralized memory elements in combination with the feedback through the environment. The underlying heterarchical architecture of the network allows to select various combinations of these elements. This modular approach representing an example of neural reuse of a limited number of procedures allows for adaptation to different internal and external conditions. A way is sketched as to how this approach may be expanded to form a cognitive system being able to plan ahead. This architecture is characterized by different types of modules being arranged in layers and columns, but the complete network can also be considered as a holistic system showing emergent properties which cannot be attributed to a specific module
Climbing favours the tripod gait over alternative faster insect gaits.
To escape danger or catch prey, running vertebrates rely on dynamic gaits with minimal ground contact. By contrast, most insects use a tripod gait that maintains at least three legs on the ground at any given time. One prevailing hypothesis for this difference in fast locomotor strategies is that tripod locomotion allows insects to rapidly navigate three-dimensional terrain. To test this, we computationally discovered fast locomotor gaits for a model based on Drosophila melanogaster. Indeed, the tripod gait emerges to the exclusion of many other possible gaits when optimizing fast upward climbing with leg adhesion. By contrast, novel two-legged bipod gaits are fastest on flat terrain without adhesion in the model and in a hexapod robot. Intriguingly, when adhesive leg structures in real Drosophila are covered, animals exhibit atypical bipod-like leg coordination. We propose that the requirement to climb vertical terrain may drive the prevalence of the tripod gait over faster alternative gaits with minimal ground contact
The Role of Reflexes Versus Central Pattern Generators
Animals execute locomotor behaviors and more with ease. They have evolved these breath-taking abilities over millions of years. Cheetahs can run, dolphins can swim and flies can fly like no artificial technology can. It is often argued that if human technology could mimic nature, then biological-like performance would follow. Unfortunately, the blind copying or mimicking of a part of nature [Ritzmann et al., 2000] does not often lead to the best design for a variety of reasons [Vogel, 1998]. Evolution works on the just good enough principle. Optimal designs are not the necessary end product of evolution. Multiple satisfactory solutions can result in similar performances. Animals do bring to our attention amazing designs, but these designs carry with them the baggage of their history. Moreover, natural design is constrained by factors that may have no relationship to human engineered designs. Animals must be able to grow over time, but still function along the way. Finally, animals are complex and their parts serve multiple functions, not simply the one we happen to examine. In short, in their daunting complexity and integrated function, understanding animal behaviors remains as intractable as their capabilities are tantalizing
Hexapod locomotion : a nonlinear dynamical systems approach
The ability of walking in a wide variety of terrains
is one of the most important features of hexapod insects. In
this paper we describe a bio-inspired controller able to generate
locomotion and switch between different type of gaits for an
hexapod robot.
Motor patterns are generated by coupled Central Pattern Generators
formulated as nonlinear oscillators. These patterns are
modulated by a drive signal, proportionally changing the oscillators
frequency, amplitude and the coupling parameters among
the oscillators. Locomotion initiation, stopping and smooth gait
switching is achieved by changing the drive signal. We also
demonstrate a posture controller for hexapod robots using the
dynamical systems approach.
Results from simulation using a model of the Chiara hexapod
robot demonstrate the capability of the controller both to
locomotion generation and smooth gait transition. The postural
controller is also tested in different situations in which the
hexapod robot is expected to maintain balance. The presented
results prove its reliability
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