Actuator Constrained Trajectory Generation and Control for Variable-Pitch Quadrotors

Control and trajectory generation algorithms for a quadrotor helicopter with variable-pitch propellers are presented. The control law is not based on near-hover assumptions, allowing for large attitude deviations from hover. The trajectory generation algorithm ts a time-parametrized polynomial through any number of way points in R3, with a closed-form solution if the corresponding way point arrival times are known a priori. When time is not specifi ed, an algorithm for fi nding minimum-time paths subject to hardware actuator saturation limitations is presented. Attitude-specifi c constraints are easily embedded in the polynomial path formulation, allowing for aerobatic maneuvers to be performed using a single controller and trajectory generation algorithm. Experimental results on a variable pitch quadrotor demonstrate the control design and example trajectories.National Science Foundation (U.S.) (Graduate Research Fellowship under Grant No. 0645960

Robotic Tracking of Coherent Structures in Flows

Lagrangian coherent structures (LCSs) are separatrices that delineate dynamically distinct regions in general dynamical systems and can be viewed as the extensions of stable and unstable manifolds to general time-dependent systems. Identifying LCS in dynamical systems is useful for many applications, including oceanography and weather prediction. In this paper, we present a collaborative robotic control strategy that is designed to track stable and unstable manifolds in dynamical systems, including ocean flows. The technique does not require global information about the dynamics, and is based on local sensing, prediction, and correction. The collaborative control strategy is implemented with a team of three robots to track coherent structures and manifolds on static flows, a time-dependent model of a wind-driven double-gyre flow often seen in the ocean, experimental data that are generated by a flow tank, and actual ocean data. We present simulation results and discuss theoretical guarantees of the collaborative tracking strategy

Experimental Validation of Robotic Manifold Tracking in Gyre-Like Flows

In this paper, we present a first attempt toward experimental validation of a multi-robot strategy for tracking manifolds and Lagrangian coherent structures (LCS) in flows. LCS exist in natural fluid flows at various scales, and they are time-varying extensions of stable and unstable manifolds of time invariant dynamical systems. In this work, we present the first steps toward experimentally validating our previously proposed real-time manifold and LCS tracking strategy that relies solely on local measurements. Although we have validated the strategy in simulations using analytical flow models, experimental flow data, and actual ocean data, the strategy has never been implemented on an actual robotic platform. We demonstrate the tracking strategy using a team of micro autonomous surface vehicles (mASVs) in our laboratory testbed and investigate the feasibility of the strategy with vehicles operating in an actual fluid environment. Our experimental results show that the team of mASVs can successfully track LCS using a simulated velocity field, and we present preliminary results showing the feasibility of a team of mASVs tracking manifolds in real flows using only local measurements obtained from their onboard flow sensors

An Experimental Testbed for Multi-Robot Tracking of Manifolds and Coherent Structures in Flows

In this paper, we describe the development of an experimental testbed capable of producing controllable ocean-like flows in a laboratory setting. The objective is to develop a testbed to evaluate multi-robot strategies for tracking manifolds and Lagrangian coherent structures (LCS) in the ocean. Recent theoretical results have shown that LCS coincide with minimum energy and minimum time optimal paths for autonomous vehicles in the ocean. Furthermore, knowledge of these structures enables the prediction and estimation of the underlying fluid dynamics. The testbed is a scaled flow tank capable of generating complex and controlled quasi-2D flow fields that exhibit wind-driven doublegyre flows. Particle image velocimetry (PIV) is used to extract the 2D surface velocities and the data is then processed to verify the existence of manifolds and Lagrangian coherent structures in the flow. The velocity data is then used to evaluate our previously proposed multi-robot LCS tracking strategy in simulation

Adaptive sampling of cumulus clouds with UAVs

International audienceThis paper presents an approach to guide a fleet of Unmanned Aerial Vehicles to actively gather data in low-altitude cumulus clouds with the aim of mapping atmospheric variables. Building on-line maps based on very sparse local measurements is the first challenge to overcome, for which an approach based on Gaussian Processes is proposed. A particular attention is given to the on-line hyperparameters optimization , since atmospheric phenomena are strongly dynamical processes. The obtained local map is then exploited by a trajectory planner based on a stochastic optimization algorithm. The goal is to generate feasible trajectories which exploit air flows to perform energy-efficient flights, while maximizing the information collected along the mission. The system is then tested in simulations carried out using realistic models of cumu-lus clouds and of the UAVs flight dynamics. Results on mapping achieved by multiple UAVs and an extensive analysis on the evolution of Gaussian Processes hyper-parameters is proposed