274 research outputs found
Herding predators using swarm intelligence
Swarm intelligence, a nature-inspired concept that includes multiplicity, stochasticity, randomness, and messiness is emergent in most real-life problem-solving. The concept of swarming can be integrated with herding predators in an ecological system. This paper presents the development of stabilizing velocity-based controllers for a Lagrangian swarm of n∈N individuals, which are supposed to capture a moving target (intruder). The controllers are developed from a Lyapunov function, total potentials, designed via Lyapunov-based control scheme (LbCS) falling under the classical approach of artificial potential fields method. The interplay of the three central pillars of LbCS, which are safety, shortness, and smoothest course for motion planning, results in cost and time effectiveness and efficiency of velocity controllers. Computer simulations illustrate the effectiveness of control laws
Bounded Distributed Flocking Control of Nonholonomic Mobile Robots
There have been numerous studies on the problem of flocking control for
multiagent systems whose simplified models are presented in terms of point-mass
elements. Meanwhile, full dynamic models pose some challenging problems in
addressing the flocking control problem of mobile robots due to their
nonholonomic dynamic properties. Taking practical constraints into
consideration, we propose a novel approach to distributed flocking control of
nonholonomic mobile robots by bounded feedback. The flocking control objectives
consist of velocity consensus, collision avoidance, and cohesion maintenance
among mobile robots. A flocking control protocol which is based on the
information of neighbor mobile robots is constructed. The theoretical analysis
is conducted with the help of a Lyapunov-like function and graph theory.
Simulation results are shown to demonstrate the efficacy of the proposed
distributed flocking control scheme
A car - like mobile manipulator with an n - link Prismatic Arm
In this research, the Lyapunov based Control Scheme (LbCS) is used to solve the motion planning and control problem of a car-like mobile robot with a long extendible prismatic arm comprising n∈N links. The prismatic arm consists of a base revolute joint and n∈N translational joints, and is mounted on the wheeled car-like mobile platform. The kinematic model of the manipulator is developed, and velocity based algorithms are utilized to firstly, move the car-like base from an initial position to its pseudo-target and secondly, maneuver the end-effector to its designated target, taking into account the restrictions and limitations of the prismatic links and the steering control laws of the system. Computer simulations are presented to illustrate the effectiveness of the proposed control laws
Lyapunov - based controllers of an n - link Prismatic Robot Arm
This research provides a generalized stabilizing velocity controllers for planer robot arm with a base rotational joint and n∈N translation joint for navigation. The end-effector of the planer robot arm has to navigate from an initial to a final configuration space in an environment, which cluttered with obstacles. The velocity controllers are developed from a Lyapunov function, total potentials, designed via Lyapunov-based control scheme (LbCS) falling under the classical approach of artificial potential fields method. The effectiveness of the controllers is validated through computer simulations
LbCS navigation controllers of Twining Lagrangian swarm individuals
This paper presents stabilizing velocity controllers for the individuals of two Lagrangian swarms, which navigates from their initial configuration space to their final configuration space, ensuring intra and inter swarm individual collision avoidance. The motion of the individuals is based on Reynold's rules of separation, alignment, and cohesion. Using the three pillars (safety, shortest and smoothest path) of Lyapunov based control scheme (LbCS), the velocity controllers of the individuals of the two swarms are derived from multiple Lyapunov functions. The effectiveness of the controllers is validated through computer simulations
Formation Control of Nonholonomic Multi-Agent Systems
This dissertation is concerned with the formation control problem of multiple agents modeled as nonholonomic wheeled mobile robots. Both kinematic and dynamic robot models are considered. Solutions are presented for a class of formation problems that include formation, maneuvering, and flocking. Graph theory and nonlinear systems theory are the key tools used in the design and stability analysis of the proposed control schemes. Simulation and/or experimental results are presented to illustrate the performance of the controllers.
In the first part, we present a leader-follower type solution to the formation maneuvering problem. The solution is based on the graph that models the coordination among the robots being a spanning tree. Our control law incorporates two types of position errors: individual tracking errors and coordination errors for leader-follower pairs in the spanning tree. The control ensures that the robots globally acquire a given planar formation while the formation as a whole globally tracks a desired trajectory, both with uniformly ultimately bounded errors. The control law is first designed at the kinematic level and then extended to the dynamic level. In the latter, we consider that parametric uncertainty exists in the equations of motion. These uncertainties are accounted for by employing an adaptive control scheme.
In the second part, we design a distance-based control scheme for the flocking of the nonholonomic agents under the assumption that the desired flocking velocity is known to all agents. The control law is designed at the kinematic level and is based on the rigidity properties of the graph modeling the sensing/control interactions among the robots. A simple input transformation is used to facilitate the control design by converting the nonholonomic model into the single-integrator equation. The resulting control ensures exponential convergence to the desired formation while the formation maneuvers according to a desired, time-varying translational velocity.
In the third part, we extend the previous flocking control framework to the case where only a subset of the agents know the desired flocking velocity. The resulting controllers include distributed observers to estimate the unknown quantities. The theory of interconnected systems is used to analyze the stability of the observer-controller system
Mobile Formation Coordination and Tracking Control for Multiple Non-holonomic Vehicles
This paper addresses forward motion control for trajectory tracking and
mobile formation coordination for a group of non-holonomic vehicles on SE(2).
Firstly, by constructing an intermediate attitude variable which involves
vehicles' position information and desired attitude, the translational and
rotational control inputs are designed in two stages to solve the trajectory
tracking problem. Secondly, the coordination relationships of relative
positions and headings are explored thoroughly for a group of non-holonomic
vehicles to maintain a mobile formation with rigid body motion constraints. We
prove that, except for the cases of parallel formation and translational
straight line formation, a mobile formation with strict rigid-body motion can
be achieved if and only if the ratios of linear speed to angular speed for each
individual vehicle are constants. Motion properties for mobile formation with
weak rigid-body motion are also demonstrated. Thereafter, based on the proposed
trajectory tracking approach, a distributed mobile formation control law is
designed under a directed tree graph. The performance of the proposed
controllers is validated by both numerical simulations and experiments
Lane changing and merging maneuvers of car-like robots
This research paper designs a unique motion planner
of multiple platoons of nonholonomic car-like robots as a feasible solution to the lane changing/merging maneuvers. The decentralized planner with a leaderless approach and a path-guidance principle derived from the Lyapunov-based control scheme generates collision free avoidance and safe merging maneuvers from multiple lanes to a single lane by deploying a split/merge strategy. The fixed obstacles
are the markings and boundaries of the road lanes, while the moving obstacles are the robots themselves. Real and virtual road lane markings and the boundaries of road lanes are incorporated into a workspace to achieve the desired formation and configuration of the robots. Convergence of the robots to goal configurations and the repulsion of the robots from specified obstacles are achieved by suitable attractive and repulsive potential field functions,
respectively. The results can be viewed as a significant contribution to the avoidance algorithm of the intelligent vehicle systems (IVS). Computer simulations highlight the effectiveness of the split/merge strategy and the acceleration-based controllers
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