8,174 research outputs found
Exponential stabilization of driftless nonlinear control systems using homogeneous feedback
This paper focuses on the problem of exponential stabilization of controllable, driftless systems using time-varying, homogeneous feedback. The analysis is performed with respect to a homogeneous norm in a nonstandard dilation that is compatible with the algebraic structure of the control Lie algebra. It can be shown that any continuous, time-varying controller that achieves exponential stability relative to the Euclidean norm is necessarily non-Lipschitz. Despite these restrictions, we provide a set of constructive, sufficient conditions for extending smooth, asymptotic stabilizers to homogeneous, exponential stabilizers. The modified feedbacks are everywhere continuous, smooth away from the origin, and can be extended to a large class of systems with torque inputs. The feedback laws are applied to an experimental mobile robot and show significant improvement in convergence rate over smooth stabilizers
Controlling rigid formations of mobile agents under inconsistent measurements
Despite the great success of using gradient-based controllers to stabilize
rigid formations of autonomous agents in the past years, surprising yet
intriguing undesirable collective motions have been reported recently when
inconsistent measurements are used in the agents' local controllers. To make
the existing gradient control robust against such measurement inconsistency, we
exploit local estimators following the well known internal model principle for
robust output regulation control. The new estimator-based gradient control is
still distributed in nature and can be constructed systematically even when the
number of agents in a rigid formation grows. We prove rigorously that the
proposed control is able to guarantee exponential convergence and then
demonstrate through robotic experiments and computer simulations that the
reported inconsistency-induced orbits of collective movements are effectively
eliminated.Comment: 10 page
Biomimetic Algorithms for Coordinated Motion: Theory and Implementation
Drawing inspiration from flight behavior in biological settings (e.g.
territorial battles in dragonflies, and flocking in starlings), this paper
demonstrates two strategies for coverage and flocking. Using earlier
theoretical studies on mutual motion camouflage, an appropriate steering
control law for area coverage has been implemented in a laboratory test-bed
equipped with wheeled mobile robots and a Vicon high speed motion capture
system. The same test-bed is also used to demonstrate another strategy (based
on local information), termed topological velocity alignment, which serves to
make agents move in the same direction. The present work illustrates the
applicability of biological inspiration in the design of multi-agent robotic
collectives
Formation control of nonholonomic mobile robots using implicit polynomials and elliptic Fourier descriptors
This paper presents a novel method for the formation control of a group of nonholonomic mobile robots using implicit and parametric descriptions of the desired formation shape. The formation control strategy employs implicit polynomial (IP) representations to generate potential fields for achieving the desired formation and the elliptical Fourier descriptors (EFD) to maintain the formation once achieved. Coordination of the robots is modeled by linear springs between each robot and its two nearest neighbors. Advantages of this new method are increased flexibility in the formation shape, scalability to different swarm sizes and easy implementation. The shape formation control is first developed for point particle robots and then extended to nonholonomic mobile robots. Several simulations with robot groups of different sizes are presented to validate our proposed approach
Nonholonomic motion planning: steering using sinusoids
Methods for steering systems with nonholonomic constraints between arbitrary configurations are investigated. Suboptimal trajectories are derived for systems that are not in canonical form. Systems in which it takes more than one level of bracketing to achieve controllability are considered. The trajectories use sinusoids at integrally related frequencies to achieve motion at a given bracketing level. A class of systems that can be steered using sinusoids (claimed systems) is defined. Conditions under which a class of two-input systems can be converted into this form are given
Quasi optimal sagittal gait of a biped robot with a new structure of knee joint
The design of humanoid robots has been a tricky challenge for several years. Due to the kinematic complexity of human joints, their movements are notoriously difficult to be reproduced by a mechanism. The human knees allow movements including rolling and sliding, and therefore the design of new bioinspired knees is of utmost importance for the reproduction of anthropomorphic walking in the sagittal plane. In this article, the kinematic characteristics of knees were analyzed and a mechanical solution for reproducing them is proposed. The geometrical, kinematic and dynamic models are built together with an impact model for a biped robot with the new knee kinematic. The walking gait is studied as a problem of parametric optimization under constraints. The trajectories of walking are approximated by mathematical functions for a gait composed of single support phases with impacts. Energy criteria allow comparing the robot provided with the new rolling knee mechanism and a robot equipped with revolute knee joints. The results of the optimizations show that the rolling knee brings a decrease of the sthenic criterion. The comparisons of torques are also observed to show the difference of energy distribution between the actuators. For the same actuator selection, these results prove that the robot with rolling knees can walk longer than the robot with revolute joint knees.ANR R2A
Fast multipole networks
Two prerequisites for robotic multiagent systems are mobility and
communication. Fast multipole networks (FMNs) enable both ends within a unified
framework. FMNs can be organized very efficiently in a distributed way from
local information and are ideally suited for motion planning using artificial
potentials. We compare FMNs to conventional communication topologies, and find
that FMNs offer competitive communication performance (including higher network
efficiency per edge at marginal energy cost) in addition to advantages for
mobility
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