14,279 research outputs found
A Distributed Model Predictive Control Framework for Road-Following Formation Control of Car-like Vehicles (Extended Version)
This work presents a novel framework for the formation control of multiple
autonomous ground vehicles in an on-road environment. Unique challenges of this
problem lie in 1) the design of collision avoidance strategies with obstacles
and with other vehicles in a highly structured environment, 2) dynamic
reconfiguration of the formation to handle different task specifications. In
this paper, we design a local MPC-based tracking controller for each individual
vehicle to follow a reference trajectory while satisfying various constraints
(kinematics and dynamics, collision avoidance, \textit{etc.}). The reference
trajectory of a vehicle is computed from its leader's trajectory, based on a
pre-defined formation tree. We use logic rules to organize the collision
avoidance behaviors of member vehicles. Moreover, we propose a methodology to
safely reconfigure the formation on-the-fly. The proposed framework has been
validated using high-fidelity simulations.Comment: Extended version of the conference paper submission on ICARCV'1
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
Decentralized Motion Planning with Collision Avoidance for a Team of UAVs under High Level Goals
This paper addresses the motion planning problem for a team of aerial agents
under high level goals. We propose a hybrid control strategy that guarantees
the accomplishment of each agent's local goal specification, which is given as
a temporal logic formula, while guaranteeing inter-agent collision avoidance.
In particular, by defining 3-D spheres that bound the agents' volume, we extend
previous work on decentralized navigation functions and propose control laws
that navigate the agents among predefined regions of interest of the workspace
while avoiding collision with each other. This allows us to abstract the motion
of the agents as finite transition systems and, by employing standard formal
verification techniques, to derive a high-level control algorithm that
satisfies the agents' specifications. Simulation and experimental results with
quadrotors verify the validity of the proposed method.Comment: Submitted to the IEEE International Conference on Robotics and
Automation (ICRA), Singapore, 201
Position-Based Multi-Agent Dynamics for Real-Time Crowd Simulation (MiG paper)
Exploiting the efficiency and stability of Position-Based Dynamics (PBD), we
introduce a novel crowd simulation method that runs at interactive rates for
hundreds of thousands of agents. Our method enables the detailed modeling of
per-agent behavior in a Lagrangian formulation. We model short-range and
long-range collision avoidance to simulate both sparse and dense crowds. On the
particles representing agents, we formulate a set of positional constraints
that can be readily integrated into a standard PBD solver. We augment the
tentative particle motions with planning velocities to determine the preferred
velocities of agents, and project the positions onto the constraint manifold to
eliminate colliding configurations. The local short-range interaction is
represented with collision and frictional contact between agents, as in the
discrete simulation of granular materials. We incorporate a cohesion model for
modeling collective behaviors and propose a new constraint for dealing with
potential future collisions. Our new method is suitable for use in interactive
games.Comment: 9 page
Decentralized formation control with connectivity maintenance and collision avoidance under limited and intermittent sensing
A decentralized switched controller is developed for dynamic agents to
perform global formation configuration convergence while maintaining network
connectivity and avoiding collision within agents and between stationary
obstacles, using only local feedback under limited and intermittent sensing.
Due to the intermittent sensing, constant position feedback may not be
available for agents all the time. Intermittent sensing can also lead to a
disconnected network or collisions between agents. Using a navigation function
framework, a decentralized switched controller is developed to navigate the
agents to the desired positions while ensuring network maintenance and
collision avoidance.Comment: 8 pages, 2 figures, submitted to ACC 201
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