3,743 research outputs found
3LP: a linear 3D-walking model including torso and swing dynamics
In this paper, we present a new model of biped locomotion which is composed
of three linear pendulums (one per leg and one for the whole upper body) to
describe stance, swing and torso dynamics. In addition to double support, this
model has different actuation possibilities in the swing hip and stance ankle
which could be widely used to produce different walking gaits. Without the need
for numerical time-integration, closed-form solutions help finding periodic
gaits which could be simply scaled in certain dimensions to modulate the motion
online. Thanks to linearity properties, the proposed model can provide a
computationally fast platform for model predictive controllers to predict the
future and consider meaningful inequality constraints to ensure feasibility of
the motion. Such property is coming from describing dynamics with joint torques
directly and therefore, reflecting hardware limitations more precisely, even in
the very abstract high level template space. The proposed model produces
human-like torque and ground reaction force profiles and thus, compared to
point-mass models, it is more promising for precise control of humanoid robots.
Despite being linear and lacking many other features of human walking like CoM
excursion, knee flexion and ground clearance, we show that the proposed model
can predict one of the main optimality trends in human walking, i.e. nonlinear
speed-frequency relationship. In this paper, we mainly focus on describing the
model and its capabilities, comparing it with human data and calculating
optimal human gait variables. Setting up control problems and advanced
biomechanical analysis still remain for future works.Comment: Journal paper under revie
Discrete Mechanics and Optimal Control Applied to the Compass Gait Biped
This paper presents a methodology for generating locally optimal control policies for simple hybrid mechanical systems, and illustrates the method on the compass gait biped. Principles from discrete mechanics are utilized to generate optimal control policies as solutions of constrained nonlinear optimization problems. In the context of bipedal walking, this procedure provides a comparative measure of the suboptimality of existing control policies. Furthermore, our methodology can be used as a control design tool; to demonstrate this, we minimize the specific cost of transport of periodic orbits for the compass gait biped, both in the fully actuated and underactuated case
Ergonomic Models of Anthropometry, Human Biomechanics and Operator-Equipment Interfaces
The Committee on Human Factors was established in October 1980 by the Commission on Behavioral and Social Sciences and Education of the National Research Council. The committee is sponsored by the Office of Naval Research, the Air Force Office of Scientific Research, the Army Research Institute for the Behavioral and Social Sciences, the National Aeronautics and Space Administration, and the National Science Foundation. The workshop discussed the following: anthropometric models; biomechanical models; human-machine interface models; and research recommendations. A 17-page bibliography is included
Gait analysis methods in rehabilitation
Introduction: Brand's four reasons for clinical tests and his analysis of the characteristics of valid
biomechanical tests for use in orthopaedics are taken as a basis for determining what
methodologies are required for gait analysis in a clinical rehabilitation context.
Measurement methods in clinical gait analysis: The state of the art of optical systems capable
of measuring the positions of retro-reflective markers placed on the skin is sufficiently advanced
that they are probably no longer a significant source of error in clinical gait analysis. Determining
the anthropometry of the subject and compensating for soft tissue movement in relation to the
under-lying bones are now the principal problems. Techniques for using functional tests to
determine joint centres and axes of rotation are starting to be used successfully. Probably the last
great challenge for optical systems is in using computational techniques to compensate for soft
tissue measurements. In the long term future it is possible that direct imaging of bones and joints
in three dimensions (using MRI or fluoroscopy) may replace marker based systems.
Methods for interpreting gait analysis data: There is still not an accepted general theory of
why we walk the way we do. In the absence of this, many explanations of walking address the
mechanisms by which specific movements are achieved by particular muscles. A whole new
methodology is developing to determine the functions of individual muscles. This needs further
development and validation. A particular requirement is for subject specific models incorporating
3-dimensional imaging data of the musculo-skeletal anatomy with kinematic and kinetic data.
Methods for understanding the effects of intervention: Clinical gait analysis is extremely
limited if it does not allow clinicians to choose between alternative possible interventions or to
predict outcomes. This can be achieved either by rigorously planned clinical trials or using
theoretical models. The evidence base is generally poor partly because of the limited number of
prospective clinical trials that have been completed and more such studies are essential. Very
recent work has started to show the potential of using models of the mechanisms by which people
with pathology walk in order to simulate different potential interventions. The development of
these models offers considerable promise for new clinical applications of gait analysis
Evolvability signatures of generative encodings: beyond standard performance benchmarks
Evolutionary robotics is a promising approach to autonomously synthesize
machines with abilities that resemble those of animals, but the field suffers
from a lack of strong foundations. In particular, evolutionary systems are
currently assessed solely by the fitness score their evolved artifacts can
achieve for a specific task, whereas such fitness-based comparisons provide
limited insights about how the same system would evaluate on different tasks,
and its adaptive capabilities to respond to changes in fitness (e.g., from
damages to the machine, or in new situations). To counter these limitations, we
introduce the concept of "evolvability signatures", which picture the
post-mutation statistical distribution of both behavior diversity (how
different are the robot behaviors after a mutation?) and fitness values (how
different is the fitness after a mutation?). We tested the relevance of this
concept by evolving controllers for hexapod robot locomotion using five
different genotype-to-phenotype mappings (direct encoding, generative encoding
of open-loop and closed-loop central pattern generators, generative encoding of
neural networks, and single-unit pattern generators (SUPG)). We observed a
predictive relationship between the evolvability signature of each encoding and
the number of generations required by hexapods to adapt from incurred damages.
Our study also reveals that, across the five investigated encodings, the SUPG
scheme achieved the best evolvability signature, and was always foremost in
recovering an effective gait following robot damages. Overall, our evolvability
signatures neatly complement existing task-performance benchmarks, and pave the
way for stronger foundations for research in evolutionary robotics.Comment: 24 pages with 12 figures in the main text, and 4 supplementary
figures. Accepted at Information Sciences journal (in press). Supplemental
videos are available online at, see http://goo.gl/uyY1R
Optimal Gait Families using Lagrange Multiplier Method
The robotic locomotion community is interested in optimal gaits for control.
Based on the optimization criterion, however, there could be a number of
possible optimal gaits. For example, the optimal gait for maximizing
displacement with respect to cost is quite different from the maximum
displacement optimal gait. Beyond these two general optimal gaits, we believe
that the optimal gait should deal with various situations for high-resolution
of motion planning, e.g., steering the robot or moving in "baby steps." As the
step size or steering ratio increases or decreases, the optimal gaits will
slightly vary by the geometric relationship and they will form the families of
gaits. In this paper, we explored the geometrical framework across these
optimal gaits having different step sizes in the family via the Lagrange
multiplier method. Based on the structure, we suggest an optimal locus
generator that solves all related optimal gaits in the family instead of
optimizing each gait respectively. By applying the optimal locus generator to
two simplified swimmers in drag-dominated environments, we verify the behavior
of the optimal locus generator.Comment: 6 page
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