Bernard Mettler

A Survey of Motion Planning Algorithms from the Perspective of Autonomous UAV Guidance

A fundamental aspect of autonomous vehicle guidance is planning trajectories. Historically, two fields have contributed to trajectory or motion planning methods: robotics and dynamics and control. The former typically have a stronger focus on computational issues and real-time robot control, while the latter emphasize the dynamic behavior and more specific aspects of trajectory performance. Guidance for Unmanned Aerial Vehicles (UAVs), including fixed- and rotary-wing aircraft, involves significant differences from most traditionally defined mobile and manipulator robots. Qualities characteristic to UAVs include non-trivial dynamics, three-dimensional environments, disturbed operating conditions, and high levels of uncertainty in state knowledge. Otherwise, UAV guidance shares qualities with typical robotic motion planning problems, including partial knowledge of the environment and tasks that can range from basic goal interception, which can be precisely specified, to more general tasks like surveillance and reconnaissance, which are harder to specify. These basic planning problems involve continual interaction with the environment. The purpose of this paper is to provide an overview of existing motion planning algorithms while adding perspectives and practical examples from UAV guidance approaches.

Nonlinear model for a small-size acrobatic helicopter

A nonlinear model for small-size helicopters was developed and validated using flight data collected on a small-size acrobatic helicopter. The model concentrates on the key effects in the dynamics of small-size helicopter, resulting in a simple model featuring a small set of physical parameters. Validation of the model by comparison of model responses to real flight-test data showed good fidelity for a wide range of conditions including acrobatic maneuvers. The model is integrated into a real-time hardware-inthe-loop simulation environment used for the development of flight control systems and path-planning algorithms that are needed for highly maneuverable autonomous small-size helicopters.

Aggressive Maneuvering of Small Autonomous Helicopters: A Human-Centered Approach

Unmanned small autonomous helicopters can perform aggressive maneuvers that will be useful for operations in challenging conditions. This paper presents an analysis of the pilot’s execution of aggressive maneuvers from flight test data, collected on an instrumented small-scale acrobatic helicopter. A full-envelope nonlinear dynamic model of the helicopter was developed and validated for aggressive maneuvering. This model was used as part of the hardware-in-the-loop simulation environment to demonstrate intuitive control strategies that were determined from the analysis of flight data. This insight will be helpful in determining closed-loop strategies for autonomous aggressive maneuvering on MIT’s platform.

Control logic for automated aerobatic flight of a miniature helicopter

In this paper we describe the control logic that enabled a small-scale unmanned helicopter to execute a completely automatic aerobatic maneuver. The logic consists of steady-state trim trajectory controllers, used prior to, and upon the exit from the maneuver; and a maneuver logic inspired by human pilot strategies. Extensive flight tests with this control logic demonstrated smooth entry into the maneuver, automatic recovery to a steady-state trim trajectory, and the robustness of the trim-trajectory control system toward measurement and modeling errors. This approach can be extended to a variety of maneuvers.

Design and applications of an avionics system for a miniature acrobatic helicopter

This paper describes the avionics developed for a miniature acrobatic helicopter and the applications for such a system. The avionics system is designed to safely achieve a robust, high-bandwidth feedback control system while meeting physical specifications. The system that is currently implemented has provided an efficient platform for testing new closed-loop controllers and has yielded critical flight data used for developing simple models of small-scale helicopter dynamics. The helicopter has already demonstrated successful flight under a body-axis velocity/heading rate-tracking controller.

ATTITUDE CONTROL OPTIMIZATION FOR A SMALL-SCALE UNMANNED HELICOPTER

This paper presents results from the attitude control optimization for a small-scale helicopter by using an identified model of the vehicle dynamics that explicitly accounts for the coupled rotor/stabilizer/fuselage (r/s/f) dynamics. The accuracy of the model is verified by showing that it successfully predicts the performance of the control system currently used for Carnegie Mellons autonomous helicopter (baseline controller). Elementary stability analysis shows that the light damping in the coupled r/s/f mode, which is due to the stabilizer bar, limits the performance of the baseline control system. This limitation is compensated by a second order notch filter. The control system is subsequently optimized using the CONDUIT control design framework with a frequency response envelope specification, which allows the attitude control performance to be accurately specified while insuring that the lightly damped r/s/f mode is adequately compensated.

Human-inspired control logic for automated maneuvering of miniature helicopter

The maneuvering control logic that was developed to implement aerobatic maneuvers fully automatically on a miniature helicopter is described. The key component of this system is a state-machine maneuver execution logic that was inspired by an analysis of human pilot strategies. Conventional multivariable trim trajectory controllers were used before and on the exit from the maneuvers; bumpless transfer between these control modes was achieved through re-initialization of controller integrator states. Flight tests with this control logic demonstrated smooth maneuver entry, automatic recovery to a steady-state trim trajectory, and an ability to sequence maneuvers in a fully autonomous airshow-like sequence. This approach was flight tested with split-S, hammerhead, and 360-deg axial roll maneuvers, as well as a split-S-hammerhead maneuver sequence. The maneuvering control logic can be used to automate a variety of other maneuvers.

Robust motion planning using a maneuver automation with built-in uncertainties

In this paper, we extend a recently introduced motion planning framework for autonomous vehicles based on a maneuver automation representation of the vehicle dynamics. We bring robustness into the guidance system by accounting for the uncertainties in the motion primitives used by the maneuver automation. The uncertainties are taken into account in the offline computation of a guidance function, as well as in a real-time planning policy. We illustrate our approach using a high-fidelity simulation model of MITs autonomous X-Cell miniature helicopter, and present an example that highlights the performance improvement over the original framework. We demonstrate that, when uncertainties are present, a nominal planning policy generates suboptimal trajectories in both open- and closed-loop guidance, and that trajectories obtained by applying the robust policy are less sensitive to perturbations in the motion primitives.

Scaling Effects and Dynamic Characteristics of Miniature Rotorcraft

The dynamic characteristics of miniature rotorcraft, starting from a parameterized linear model developed for the identification of a Yamaha R-50 helicopter (3.04-m rotor diameter), and later applied to a smaller, more agile X-Cell .60 helicopter (1.52-m rotor diameter), are described. From this model, key flying qualities metrics are extracted and related to physical parameters. Based on these metrics, the identified data, and fundamental Froude and Mach scaling hypotheses, the effects of rotorcraft size on flying qualities and performance characteristics are analyzed and scaling trends inferred. These results are used to highlight the mechanical features and flight characteristics that are typical of small-scale rotorcraft, as well as to provide basic design guidelines for this class of vehicles.

Nonlinear trajectory generation for autonomous vehicles via parameterized maneuver classes

A technique is presented for creating continuously parameterized classes of feasible system trajectories. These classes, which are useful for higher-level vehicle motion planners, follow directly from a small collection of userprovided example motions. A dynamically feasible trajectory interpolation algorithm generates a continuous family of vehicle maneuvers across a range of boundary conditions while enforcing nonlinear system equations of motion as well as nonlinear equality and inequality constraints. The scheme is particularly useful for describing motions that deviate widely from the range of linearized dynamics and where satisfactory example motions may be found from off-line nonlinear programming solutions or motion capture of human-piloted flight. The interpolation algorithm is computationally efficient, making it a viable method for real-time maneuver synthesis, particularly when used in concert with a vehicle motion planner. Experimental application to a three-degree-of-freedom rotorcraft test bed demonstrates the essential features of system and trajectory modeling, maneuver example selection, maneuver class synthesis, and integration into a hybrid system path planner.