16,114 research outputs found
Circular formation control of fixed-wing UAVs with constant speeds
In this paper we propose an algorithm for stabilizing circular formations of
fixed-wing UAVs with constant speeds. The algorithm is based on the idea of
tracking circles with different radii in order to control the inter-vehicle
phases with respect to a target circumference. We prove that the desired
equilibrium is exponentially stable and thanks to the guidance vector field
that guides the vehicles, the algorithm can be extended to other closed
trajectories. One of the main advantages of this approach is that the algorithm
guarantees the confinement of the team in a specific area, even when
communications or sensing among vehicles are lost. We show the effectiveness of
the algorithm with an actual formation flight of three aircraft. The algorithm
is ready to use for the general public in the open-source Paparazzi autopilot.Comment: 6 pages, submitted to IROS 201
Decentralized MPC based Obstacle Avoidance for Multi-Robot Target Tracking Scenarios
In this work, we consider the problem of decentralized multi-robot target
tracking and obstacle avoidance in dynamic environments. Each robot executes a
local motion planning algorithm which is based on model predictive control
(MPC). The planner is designed as a quadratic program, subject to constraints
on robot dynamics and obstacle avoidance. Repulsive potential field functions
are employed to avoid obstacles. The novelty of our approach lies in embedding
these non-linear potential field functions as constraints within a convex
optimization framework. Our method convexifies non-convex constraints and
dependencies, by replacing them as pre-computed external input forces in robot
dynamics. The proposed algorithm additionally incorporates different methods to
avoid field local minima problems associated with using potential field
functions in planning. The motion planner does not enforce predefined
trajectories or any formation geometry on the robots and is a comprehensive
solution for cooperative obstacle avoidance in the context of multi-robot
target tracking. We perform simulation studies in different environmental
scenarios to showcase the convergence and efficacy of the proposed algorithm.
Video of simulation studies: \url{https://youtu.be/umkdm82Tt0M
Coordinated task manipulation by nonholonomic mobile robots
Coordinated task manipulation by a group of autonomous mobile robots has received signicant research effort in the last decade. Previous studies in the area revealed that one of the main problems in the area is to avoid the collisions of the robots with obstacles as well as with other members of the group. Another problem is to come up with a model for successful task manipulation. Signicant research effort has accumulated on the denition of forces to generate reference trajectories for each autonomous mobile robots engaged in coordinated behavior. If the mobile robots are nonholonomic, this approach fails to guarantee successful manipulation of the task since the so-generated reference trajectories might not satisfy the nonholonomic constraint. In this work, we introduce a novel coordinated task manipulation model inclusive of an online collision avoidance algorithm. The reference trajectory for each autonomous nonholonomic mobile robot is generated online in terms of linear and angular velocity references for the robot; hence these references automatically satisfy the nonholonomic constraint. The generated reference velocities inevitably depend on the nature of the specied coordinated task. Several coordinated task examples, on the basis of a generic task, have been presented and the proposed model is veried through simulations
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