Adaptive Vision-Based Guidance Law with Guaranteed Performance Bounds

The article of record as published may be found at https://doi.org/10.2514/1.46287This work discusses vision-based tracking of a ground vehicle moving with unknown time-varying velocity. The follower unmanned aerial vehicle is equipped with a single camera. The control objective is to regulate the two- dimensional horizontal range between the unmanned aerial vehicle and the target to a constant. The contribution of this paper has two distinct features. The developed guidance law uses the estimates of the target’s velocity obtained from a fast-estimation scheme. It is shown that the fast-estimation scheme has guaranteed performance bounds and the tracking performance bound can be explicitly derived as a function of the estimation error. The performance bounds imply that the signals of the closed-loop adaptive system remain close to the corresponding signals of a bounded closed-loop reference system, both in transient and steady-state responses. The reference system is introduced solely for the purpose of analysis. This paper also analyzes the stability and the performance degradation of the closed-loop adaptive system in the presence of out-of-frame events, when continuous extraction of the target’s information is not feasible due to failures in the image-processing module. The feedback loop is then closed using the frozen estimates. The out-of-frame events are modeled as brief instabilities. A sufficient condition for the switching signal is derived that guarantees graceful degradation of performance during target loss. The results build upon the earlier-developed fast-estimation scheme of the target’s velocity, the inverse-kinematics-based guidance law, and insights from switching systems theory

Time-Critical Cooperative Path Following of Multiple UAVs over Time-Varying Networks

submitted to AIAA Journal of Guidance, Control and Dynamic

Time-Critical Cooperative Path Following of Multiple UAVs: Case Studies

This paper describes a multi-vehicle motion control framework for time-critical cooperative missions and evaluates its performance by considering two case stud- ies: a simultaneous arrival mission scenario and a sequential auto-landing of a fleet of UAVs. In the adopted setup, the UAVs are assigned nominal spatial paths and speed profiles along those, and the vehicles are then tasked to execute co- operative path following, rather than “open-loop” trajectory-tracking maneuvers. This cooperative strategy yields robust behavior against external disturbances by allowing the UAVs to negotiate their speeds along the paths in response to coordi- nation information exchanged over the supporting communications network. The approach applies to teams of heterogeneous vehicles and does not necessarily lead to swarming behavior

Coordinated Path Following of Multiple UAVs for Time-Critical Missions in the Presence of Time-Varying Communication Topologies

We address the problem of steering multiple unmanned air vehicles (UAVs) along given paths (path-following) under strict temporal coordination constraints requiring, for example, that the vehicles arrive at their final destinations at exactly the same time. Pathfollowing relies on a nonlinear Lyapunov based control strategy derived at the kinematic level with the augmentation of existing autopilots with L1 adaptive output feedback control laws to obtain inner-outer loop control structures with guaranteed performance. Multiple vehicle timecritical coordination is achieved by enforcing temporal constraints on the speed profiles of the vehicles along their paths in response to information exchanged over a dynamic communication network. We consider that each vehicle transmits its coordination state to only a subset of the other vehicles, as determined by the communications topology adopted. We address explicitly the case where the communication graph that captures the underlying communication network topology may be disconnected during some interval of time (or may even fail to be connected at any instant of time) and provide conditions under which the closed-loop system is stable. Flight test results obtained at Camp Roberts, CA in 2008 and hardware-in-the-loop (HITL) simulations demonstrate the benefits of the algorithms developed

Cooperative Path-Following of Multiple Multirotors over Time-Varying Networks

The article of record as published may be found at https://doi.org/10.1109/TASE.2015.2406758This paper addresses the problem of time-coordina- tion of a team of cooperating multirotor unmanned aerial vehicles that exchange information over a supporting time-varying net- work. A distributed control law is developed to ensure that the vehicles meet the desired temporal assignments of the mission, while flying along predefined collision-free paths, even in the pres- ence of faulty communication networks, temporary link losses, and switching topologies. In this paper, the coordination task is solved by reaching consensus on a suitably defined coordination state. Conditions are derived under which the coordination errors converge to a neighborhood of zero. Simulation and flight test results are presented to validate the theoretical findings

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

The article of record as published may be found at https://doi.org/10.2514/1.56538This 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 of time or even fails to be connected at all times. Conditions are given under which the cooperative path-following closed-loop system is stable. Flight test results of a coordinated road-search mission demonstrate the efficacy of the multi-vehicle cooperative control framework developed in the paper