Vladimir Dobrokhodov

Vision-based tracking and motion estimation for moving targets using small UAVs

This paper addresses the development of a vision-based target tracking system for a small unmanned air vehicle. The algorithm performs autonomous tracking of a moving target, while simultaneously estimating GPS coordinates of the target. A low cost off the shelf system is utilized, with a modified radio controlled aircraft airframe, gas engine and servos. Tracking is enabled using a low-cost, miniature pan-tilt gimbal. The control algorithm provides rapid and sustained target acquisition and tracking capability. A target position estimator was designed and shown to provide reasonable targeting accuracy. The impact of target loss events on the control and estimation algorithms is analyzed in detail

Path following for unmanned aerial vehicles using L1 adaptive augmentation of commercial autopilots

The paper presents a three-dimensional path-following control algorithm that expands the capabilities of conventional autopilots, which are normally designed to provide only guidance loops for waypoint navigation. Implementation of this algorithm broadens the range of possible applications of small unmanned aerial vehicles. The solution proposed takes explicit advantage of the fact that normally these vehicles are equipped with autopilots stabilizing the vehicles and providing angular-rate tracking capabilities. Therefore, the overall closed-loop system exhibits naturally an inner-outer (dynamics-kinematics) control loop structure. The outer-loop path-following control law developed relies on a nonlinear control strategy derived at the kinematic level, while the inner-loop consisting of the autopilot together with an L1 adaptive augmentation loop is designed to meet strict performance requirements in the presence of unmanned aerial vehicle modeling uncertainty and environmental disturbances. A rigorous proof of stability and performance of the path-following closed-loop system, including the dynamics of the unmanned aerial vehicle with its autopilot, is given. The paper bridges the gap between theory and practice and includes results of extensive flight tests performed in Camp Roberts, California, which demonstrate the benefits of the framework adopted for the control system design.

Coordinated Path Following for Time-Critical Missions of Multiple UAVs via L1 Adaptive Output Feedback Controllers

This paper develops a complete framework for coordinated control of multiple unmanned air vehicles (UAVs) that are tasked to execute collision-free maneuvers under strict spatial and temporal constraints in restricted airspace. The framework proposed includes strategies for deconicted real-time path generation, nonlinear path following, and multiple vehicle coordination. Path following relies on the augmentation of existing autopilots with L1 adaptive output feedback control laws to obtain inner-outer loop control structures with guaranteed performance. Multiple vehicle coordination is achieved by enforcing temporal constraints on the speed proles of the vehicles along their paths in response to information exchanged over a communication network. Again, L1 adaptive control is used to yield an inner-outer loop structure for vehicle coordination. A rigorous proof of stability and performance bounds of the combined path following and coordination strategies is given. Flight test results obtained at Camp Roberts, CA in 2007 demonstrate the benets of using L1 adaptive control for path following of a single vehicle. Hardware-in-the-loop simulations for two vehicles are discussed and provide a proof of concept for time-critical coordination of multiple vehicles over communication networks with xed topologies.

On Vision-Based Target Tracking and Range Estimation for Small UAVs

*† ‡ § Development of a vision-based target tracking algorithm for an unmanned air vehicle is described. The algorithm provides an autonomous target tracking capability, while simultaneously estimating GPS coordinates of the target. A low cost, primarily COTS system is utilized, with a modified RC aircraft airframe, gas engine and servos. Tracking is enabled using a low-cost, miniature pan-tilt gimbal, driven by COTS servos and electronics. The control algorithm provides rapid and sustained target acquisition and tracking capability. A target position estimator was designed and shown to provide reasonable targeting accuracy. Impact of target loss events on the control and estimation algorithms is analyzed in detail.

Vision-Based Tracking and Motion Estimation for Moving Targets Using Unmanned Air Vehicles

This paper addresses the development of a vision-based target tracking system for a small unmanned air vehicle. The algorithm performs autonomous tracking of a moving target, while simultaneously estimating geographic coordinates, speed, and heading of the target Tight real-time integration of unmanned air vehicles video and telemetry data streams with georeferenced database allows for reliable target identification, increased precision, and shortened time of target motion estimation. A low-cost off-the-shelf system is used, with a modified radiocontrolled aircraft airframe, gas engine, and servos. Tracking is enabled using a low-cost, miniature pan-tilt gimbal. The control algorithm provides rapid target acquisition and tracking capability. A target motion estimator was designed and shown in multiple flight tests to provide reasonable targeting accuracy. The impact of tracking loss events on the control and estimation algorithms is analyzed in detail.

Time-Critical Cooperative Path Following of Multiple Unmanned Aerial Vehicles over Time-Varying Networks

This paper addresses the problem of steering a fleet of unmanned aerial vehicles along desired three-dimensional paths while meeting stringent spatial and temporal constraints. A representative example is the challenging mission scenario where the unmanned aerial vehicles are tasked to cooperatively execute collision-free maneuvers and arrive at their final destinations at the same time. In the proposed framework, the unmanned aerial vehicles are assigned nominal spatial paths and speed profiles along those, and then the vehicles are requested to execute cooperative path following, rather than open loop trajectory tracking maneuvers. This strategy yields robust behavior against external disturbances by allowing the unmanned aerial vehicles to negotiate their speeds along the paths in response to information exchanged over the supporting communications network. The paper considers the case where the graph that captures the underlying time-varying communications topology is disconnected during some interval...

Time-Critical Cooperative Control of Multiple Autonomous Vehicles: Robust Distributed Strategies for Path-Following Control and Time-Coordination over Dynamic Communications Networks

Worldwide, there has been growing interest in the use of autonomous vehicles to execute missions of increasing complexity without constant supervision of human operators. A key enabling element for the execution of such missions is the availability of advanced systems for motion control of autonomous vehicles. Usually, the problems of motion control for a single autonomous vehicle are roughly classified into three groups:.

Stabilization of Cascaded Systems via L1 Adaptive Controller with Application to a UAV Path Following Problem and Flight Test Results

This paper presents a theoretical framework for augmenting an existing autopilot by an adaptive element so that it tracks a given smooth reference command with desired specifications. The main contribution of the approach is that it allows for augmenting the autopilot without any modifications to it. The augmentative adaptive element is based on the L1 adaptive output feedback control architecture developed in [1]. The complete path following architecture of this paper enables a UAV with an off-the-shelf autopilot to follow a predetermined path that it was not otherwise designed to follow. The paper concludes with flight test results performed in Camp Roberts, CA, in February of 2007.

Six-Degree-of-Freedom Model of a Controlled Circular Parachute

Abstract : The paper continues a series of publications devoted to modern advances in aerodynamic decelerator system technology started recently (Journal of Aircraft, Vol. 38, No. 5, 2001) and addresses the development of a six-degree- of-freedom model of a guided circular parachute. The paper reviews existing circular parachute models and discusses several modeling issues unresolved within the frame of existing approaches or completely ignored so far. These issues include using data obtained in the aerodynamic experiments and computational-fluid-dynamics modeling for both undistorted (uncontrolled) and distorted (controlled) canopy shapes, introducing and computing control derivatives, and providing comparison with the real flight data. The paper provides step-by-step development of the mathematical model of circular parachute that includes the basic equations of motion, analysis and computation of the aerodynamic forces and moments, and investigation with modeling of special modes observed in flight. It then introduces a new application of a two-step aerodynamic parameters identification algorithm that is based on comparison with two types of the air-drop data (uncontrolled set and controlled one). The paper ends with summary of the obtained results and proposes a vital direction for the further elaboration of the developed model.

Vision-based target tracking and motion estimation using a small UAV

This work extends the earlier results on passive vision-based tracking and motion estimation of a ground vehicle. The follower small unmanned air vehicle (UAV) is equipped with a single gimbaled pan/tilt camera and a high bandwidth wireless link for video and command transmitting. The objective is for the UAV to maintain a horizontal circular orbit about the target with a predefined radius and to concurrently provide real-time estimation of the targets position, speed and heading. The target velocity estimation problem is formulated such that the recently developed ℒ1 fast adaptive estimator can be applied. We give a rigorous proof of asymptotic stability for the guidance law for the static target case, and provide a reformulation of the control objective for the moving target case so that the existing controller can be applied naturally.