Florian-Michael Adolf

An Unmanned Helicopter for Autonomous Flights in Urban Terrain

This work summarizes a multi-disciplinary research project, focusing on key enabling techniques towards true autonomous flight of small, low flying VTOL UAVs. Research activities cover the flying testbed, a simulation and testing environment, as well as integrated components for onboard navigation, perception, planning and control. Promising results and feasibility demonstrations in flight tests underline the successful domain specific enhancements of approaches based on aeronautical engineering, computer science and mobile robotics. The current approaches pave the way towards further research in improved flight control performance and more system autonomy when a-priori mission uncertainties increase.

Autonomous Vision-Based Helicopter Flights Through Obstacle Gates

The challenge for unmanned aerial vehicles to sense and avoid obstacles becomes even harder if narrow passages have to be crossed. An approach to solve a mission scenario that tackles the problem of such narrow passages is presented here. The task is to fly an unmanned helicopter autonomously through a course with gates that are only slightly larger than the vehicle itself. A camera is installed on the vehicle to detect the gates. Using vehicle localization data from a navigation solution, camera alignment and global gate positions are estimated simultaneously. The presented algorithm calculates the desired target waypoints to fly through the gates. Furthermore, the paper presents a mission execution plan that instructs the vehicle to search for a gate, to fly through it after successful detection, and to search for a proceeding one. All algorithms are designed to run onboard the vehicle so that no interaction with the ground control station is necessary, making the vehicle completely autonomous. To develop and optimize algorithms, and to prove the correctness and accuracy of vision-based gate detection under real operational conditions, gate positions are searched in images taken from manual helicopter flights. Afterwards, the integration of visual sensing and mission control is proven. The paper presents results from full autonomous flight where the helicopter searches and flies through a gate without operator actions.

A Decoupled Approach for Trajectory Generation for an Unmanned Rotorcraft

A decoupled approach to trajectory generation based on a cubic spline geometry formulation is introduced. The distinct consideration of boundary conditions yields a continuously differentiable trajectory definition such that path tracking errors are minimized during flight. A curvature-based, dimensionless space-filling curve allows to determine a suitable velocity profile along the path for hover-capable vehicles. Tracking of the trajectory is enabled by a conversion between the spline parameters and the arc length of the spline. In the past years, this approach in combination with a suitable trajectory tracking control has been successfully flight tested with an unmanned helicopter.

A Sequence Control System for Onboard Mission Management of an Unmanned Helicopter

This paper presents a solution to the onboard mission management problem for UAVs. Inspired by successful approaches from the mobile robotics domain, the proposed architecture achieves hybrid control by combining ideas from the behavior-based paradigm and a three-layered high-level control architectures. A Sequence Control System implements the essential components of this architecture. It is open with respect to its interfaces to other onboard components (e.g. the obstacle avoidance system). Events and commands sent by a remote operator or an onboard component can be integrated into the system in a plug-andfly fashion. A remote operator can send direct commands on different abstraction levels. The solutions to more complex mission problems and events (e.g. onboard trajectory planning or reacting on a data link loss) can be delegated using high level commands. To assure the safe operation of the Sequence Control System, the system is characterized by multiple techniques. First, the event-based decision logic is modeled as a State Chart model. Second, a truth table of valid external commands assures that only permitted commands are accepted by the event handling. Finally, a grammar-based plausibility check avoids illegal behavior commands within a mission plan. The system is implemented onboard the UAVs of the ARTIS program. It is validated in unit tests, and tested in software-in-the-loop and hardware-in-the-loop simulations. As a result, the system allows a robust, deterministic high level control of UAVs. It allows an operator to control a UAV at different levels of autonomy, ranging from common joystick control to execution of prearranged missions.

Mapping and path planning in complex environments: An obstacle avoidance approach for an unmanned helicopter

This paper presents an obstacle avoidance method that is performed with an unmanned helicopter. The approach begins with a mapping step where information from sensor data about previously unknown dangers is extracted into an occupancy grid and eventually converted into a polygonal 3D world model. This continuously updating map is used by a path planner that generates and updates a 3D trajectory guiding the vehicle through safe passages around the detected objects. The algorithms are generic but optimized for unmanned aircraft and a stereo camera as the environmental sensor. Computation is fully executed on board so that a ground control station is only needed for supervision. With successful obstacle detection and avoidance flight tests, the paper shows the qualification of the presented method under real operational conditions.

Meshing and Simplification of High Resolution Urban Surface Data for UAV Path Planning

This work presents an approach to utilize high resolution surface data as a-priori information for three dimensional path planning at very low altitude. The major challenge is preserve features while reducing the amount of data to a minimum. Non significant height points are eliminated by a neighbor search, performed within a data structure generated from pseudo 3D Delaunay meshing. A comparison to an alternatively implemented simplification shows which inherent building features can be preserved. For highlighting the feasibility of the approach, the processing results of real urban surface data from the inner city of Berlin is presented and used for sampling based path planning of an unmanned helicopter.

Rapid Multi-Query Path Planning For A Vertical Take-Off and Landing Unmanned Aerial Vehicle

This paper presents an online approach for multi-query path planning that enables an unmanned aircraft to quickly react to newly located or changed obstacles. All three spatial dimensions are considered during planning, as it is likely to be necessary for urban terrain with overhangs or inside buildings.Asampling-based motion planning approach is combined with an anytime path search such that an online trade-off between path optimality and rapid path computation is possible. The presented global path planner can rapidly handle global cost changes acquired during flight. Moreover, the multi-query property of the planning system supports combinatorial optimization problems such that the decisional autonomy is maximized during flight. This increase in system autonomy is achieved for holonomic maneuvering through scenes with unforeseen obstacle changes. This way, a common constraining requirement for unmanned aircraft can be relaxed: with onboard sensing and planning capabilities, a highly reliable, real-time remote control link is not necessary to ensure collision-free flight and higher level decision-making.

Certification and Software Verification Considerations for Autonomous Unmanned Aircraft

Software verification for highly automatic unmanned aerial vehicles is not only a problem itself, it is furthermore constrained by certification standards and regulatory rules. These, however, are themselves still under development. As a top-level view, the current status of unmanned aerial vehicle verification, certification, and regulation is addressed and corresponding challenges are discussed. From a low-level view, this work presents the processes and tools that were established for the software development, verification, and validation of the unmanned rotorcraft software testbed ARTIS. Large efforts have been put into the software verification process to cope with the growing complexity of the autonomous system and the validation of the software behavior. Automated tests drive the development of the mission planning, mission management, and sensor fusion systems. High-level behavior is tested by complex simulation scenarios. To connect the aforementioned top- and low-level views, a comparison betwee...

Onboard Mission Management for a VTOL UAV Using Sequence and Supervisory Control

This chapter addresses the challenges of onboard mission management for small, low flying UAVs in order to reduce their dependency on reliable remote control. The system presented and tested onboard an unmanned aerial vehicle (UAV) provides levels of autonomy, scalable at runtime either by the operator or due to the absence of a data link. This way, it is a feasible approach towards autonomous flight guidance within the low-altitude domain (e.g. urban areas) where unpredictable events are likely to require onboard decision-making. In the following sections the problems of onboard mission management, embedded high level architectures and their implementation issues are discussed. The design of a onboard Mission Management System for a test platform with vertical take-off and landing (VTOL) capabilities is presented, followed by discussions of the implemented system and a research outlook.

PROBABILISTIC ROADMAPS AND ANT COLONY OPTIMIZATION FOR UAV MISSION PLANNING

This paper presents a two-tiered approach to mission planning based on Probabilistic Roadmaps for path planning and Ant Colony Optimization for task planning. The path planner searches paths in a finite, obstacle-constrained three dimensional space whereas the task planner determines a near optimal task order for a set of tasks and a group of heterogeneous agents. The mission planning system is employed in an unmanned helicopter project that researches on intelligent technologies for small, low-altitude aerial vehicles. Results from simulation experiments demonstrate the feasibility of combining a dedicated path planner with a task planner.