530 research outputs found
Influence of frictions on gait optimization of a biped robot with an anthropomorphic knee
This paper presents the energy consumption of a biped robot with a new modelled structure of knees which is called rolling knee (RK). The dynamic model, the actuators and the friction coefficients of the gear box are known. The optimal energy consumption can also be calculated. The first part of the paper is to validate the new kinematic knee on a biped robot by comparing the energy consumption during a walking step of the identical biped but with revolute joint knees. The cyclic gait is given by a succession of Single Support Phase (SSP) followed by an impact. The gait trajectories are parameterized by cubic spline functions. The energetic criterion is minimized through optimization while using the simplex algorithm and Lagrange penalty functions to meet the constraints of stability and deflection of the mobile foot. An analysis of the friction coefficients is done by simulation to compare the human characteristics to the robot with RK. The simulation results show an energy consumption reduction through the biped with rolling knee configuration. The influence of friction coefficients shows the energy consumption of biped robot is close to that of the human.ANR-09-SEGI-011-R2A2; French National Research Agenc
Asymptotically Stable Walking of a Five-Link Underactuated 3D Bipedal Robot
This paper presents three feedback controllers that achieve an asymptotically
stable, periodic, and fast walking gait for a 3D (spatial) bipedal robot
consisting of a torso, two legs, and passive (unactuated) point feet. The
contact between the robot and the walking surface is assumed to inhibit yaw
rotation. The studied robot has 8 DOF in the single support phase and 6
actuators. The interest of studying robots with point feet is that the robot's
natural dynamics must be explicitly taken into account to achieve balance while
walking. We use an extension of the method of virtual constraints and hybrid
zero dynamics, in order to simultaneously compute a periodic orbit and an
autonomous feedback controller that realizes the orbit. This method allows the
computations to be carried out on a 2-DOF subsystem of the 8-DOF robot model.
The stability of the walking gait under closed-loop control is evaluated with
the linearization of the restricted Poincar\'e map of the hybrid zero dynamics.
Three strategies are explored. The first strategy consists of imposing a
stability condition during the search of a periodic gait by optimization. The
second strategy uses an event-based controller. In the third approach, the
effect of output selection is discussed and a pertinent choice of outputs is
proposed, leading to stabilization without the use of a supplemental
event-based controller
Bayesian Gait Optimization for Bipedal Locomotion
One of the key challenges in robotic bipedal locomotion is finding gait parameters that optimize a desired performance criterion, such as speed, robustness or energy efficiency. Typically, gait optimization requires extensive robot experiments and specific expert knowledge. We propose to apply data-driven machine learning to automate and speed up the process of gait optimization. In particular, we use Bayesian optimization to efficiently find gait parameters that optimize the desired performance metric. As a proof of concept we demonstrate that Bayesian optimization is near-optimal in a classical stochastic optimal control framework. Moreover, we validate our approach to Bayesian gait optimization on a low-cost and fragile real bipedal walker and show that good walking gaits can be efficiently found by Bayesian optimization. © 2014 Springer International Publishing
An Energy Efficient Knee Locking Mechanism for a Dynamically Walking Robot
In this work, we present the design and the implementation of an innovative knee locking mechanism for a dynamically walking robot. The mechanism consists of a four-bar linkage that realizes a mechanical singularity for locking the knee when the leg is in the extended position. Once extended, the knee remains locked without energy consumption, while unlocking it only costs a small amount of energy. Tests showed that the robot walks robustly and that the energy consumption of the new system is low
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
Straight-Leg Walking Through Underconstrained Whole-Body Control
We present an approach for achieving a natural, efficient gait on bipedal
robots using straightened legs and toe-off. Our algorithm avoids complex height
planning by allowing a whole-body controller to determine the straightest
possible leg configuration at run-time. The controller solutions are biased
towards a straight leg configuration by projecting leg joint angle objectives
into the null-space of the other quadratic program motion objectives. To allow
the legs to remain straight throughout the gait, toe-off was utilized to
increase the kinematic reachability of the legs. The toe-off motion is achieved
through underconstraining the foot position, allowing it to emerge naturally.
We applied this approach of under-specifying the motion objectives to the Atlas
humanoid, allowing it to walk over a variety of terrain. We present both
experimental and simulation results and discuss performance limitations and
potential improvements.Comment: Submitted to 2018 IEEE International Conference on Robotics and
Automatio
Doctor of Philosophy
dissertationThis dissertation defines a new class of climbing robots, steering-plane bipeds, which encompasses a large number of existing climbing robots. Three major levels of motion planning are characterized which are common to this class of robots, namely, path planning, step planning, and gait planning. The unified presentation of related motion planning techniques is more generally applicable and more thorough than related algorithms in other literature, while more explicitly identifying limitations and tradeoffs due to alternate design choices within the class of steering-plane bipeds. A novel spline-based method for generating gaits is presented which uses separate path and time rate controls, and explicitly defined foot approach and departure directions that allows 1) a nominal guarantee of collision-free foot trajectories when close to the desired step configuration, 2) independent control of gait shape and speed, and 3) a unified representation of the four gait families of steering-plane bipeds: flipping, inchworm, step-through, and spinning gaits. This dissertation presents a thorough examination of the variations within each gait family, rather than merely presenting a representative instance of each. Concrete case studies applying the techniques of this dissertation are presented for optimizing the gaits for overall speed, energy efficiency, and minimum gripping force and moment. The results highlight that many common gaits in the literature are far from optimal. Results and general rules of thumb for gait planning are extracted that allow guidance for obtaining good results even if using alternate planning techniques without optimization
A literature review on the optimization of legged robots
Over the last two decades the research and development of legged locomotion robots has grown steadily. Legged
systems present major advantages when compared with ‘traditional’ vehicles, because they allow locomotion in inaccessible
terrain to vehicles with wheels and tracks. However, the robustness of legged robots, and especially their energy
consumption, among other aspects, still lag behind mechanisms that use wheels and tracks. Therefore, in the present
state of development, there are several aspects that need to be improved and optimized. Keeping these ideas in mind,
this paper presents the review of the literature of different methods adopted for the optimization of the structure
and locomotion gaits of walking robots. Among the distinct possible strategies often used for these tasks are referred
approaches such as the mimicking of biological animals, the use of evolutionary schemes to find the optimal parameters
and structures, the adoption of sound mechanical design rules, and the optimization of power-based indexes
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