Figure 5 - uploaded by Sanjiv Singh
Content may be subject to copyright.
Obstacle avoidance scenario. During a test flight on the ULB, the Trajectory Planner successfully planned a trajectory around an obstacle detected by the Perception System. Inset shows the real-time Perception system output and planned trajectory. The ULB received and tracked this maneuver in real time, avoiding the peak.
Source publication
This paper describes the Tactical Autonomous Aerial LOgistics System (TALOS), developed and flight tested during the first phase of the Office of Naval Research (ONR) Autonomous Aerial Cargo/Utility System (AACUS) Innovative Naval Prototype (INP) program. The ONR vision for AACUS is to create a retrofit perception/planning/human interface system th...
Context in source publication
Context 1
... Trajectory Planning features are detailed in References 17, 18, and 19, and include (1) the ability to apply parallel, alternate trajectory planning techniques in an 'ensemble' and choose the best solution, (2) guaranteed safety through the inclusion of a library of deterministic safety maneuvers, and (3) specialized techniques to enable landing into difficult environments with winds. Figure 5 shows a typical result. ...
Citations
... Shortly thereafter, another example of reactive autonomy was first flown on the full-authority Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) JUH-60A Fly-by-Wire (FBW) Black Hawk helicopter in mountainous terrain [11,12]. The Office of Naval Research (ONR) Autonomous Aerial Cargo/Utility System (AACUS) program also addressed autonomous obstacle avoidance and landing at unprepared sites [13]. An emphasis of this program was portability, so the autonomy system was tested on a variety of partial-authority aircraft including the Boeing AH-6 Unmanned Little Bird (ULB), Bell 206 variants, and Aurora's Bell UH-1. ...
... An example of autonomy on a partial-authority system was that used on the Boeing ULB [13], which had a mode to follow waypoint trajectories generated by the autonomy. This system was based on the previously mentioned autonomy work in Ref. [10], and relied on commanding dual electromechanical actuators composed of a low and high bandwidth unit [18]. ...
A comparison of a guidance and flight control system performance on a partial-authority helicopter was made against a previously flown version on a full-authority helicopter. This control system was integrated and flight-tested on a partial-authority helicopter to autonomously navigate and reactively avoid obstacles enroute and on final landing approach. Because both systems used virtually the same control system and aircraft, a comparison was performed to
investigate how much of the autonomous maneuvering capability could be recovered using a partial-authority aircraft. This paper describes the control system, its performance, and how it was adapted to a partial-authority EH-60L Black Hawk helicopter. A partial-authority mixing method is described and it was used to integrate the
autonomy system using frequency allocation to distribute the control commands to the high- and low-frequency actuation. Flight tests results are presented of the integrated system flying predefined maneuvers that ranged from precision hover maneuvers to moderately aggressive forward flight maneuvers. Results are also presented of the system navigating through mountainous terrain using a reactive obstacle-avoidance algorithm. Tracking performance, actuator usage, and stability results for both systems are shown. The comparison of the partial- and full-authority results showed that the partial-authority mixing system was effective by allowing the partial-authority system to achieve most of the full-authority performance as measured by path tracking error and actuator usage for several autonomous maneuvers.
... Eventually, LADAR (aka LiDAR or LIDAR)-based autonomous landing algorithms progressed onto full-scale rotorcraft such as was tested on the Boeing Unmanned Little Bird (ULB), in Ref. 7 and on the Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) JUH-60A Black Hawk helicopter in Ref. 8. More recently, full-scale SLAD work was conducted in Ref. 9, as part of the Office of Naval Research, Autonomous Aerial Cargo/Utility System (AACUS) prototype program. This program also used the ULB with a landing system using a scanning LADAR, electro-optical and infrared cameras, and integrated GPS-INS to georectify the LADAR returns. ...
... This program also used the ULB with a landing system using a scanning LADAR, electro-optical and infrared cameras, and integrated GPS-INS to georectify the LADAR returns. Follow-on work in perception was presented in Ref. 10, where improvements were made to the algorithm in Ref. 9 that were related to wire-detection, GPS free navigation, and, LZ categorization. ...
An important element in autonomous full-scale rotorcraft operations is safe landing area determination (SLAD) to find landing points at unprepared sites. This capability is also critical for optionally piloted rotorcraft where landing aides are essential for operations in severely degraded visual environments. This paper presents flight-test results from a new SLAD algorithm flown on the Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) JUH-60A Black Hawk helicopter equipped with a nodding line-scanning LADAR. Eighty-six autonomous and manned approaches were flown to landing zones, many in rugged mountainous terrain. A detailed description of the algorithm and flight hardware is given, and sample results are shown for seven landing zones. Pilot interaction with the algorithm during approach and final landing point selection is also discussed.
... The Office of Naval Research (ONR) Autonomous Aerial Cargo/Utility System (AACUS) program addressed autonomous obstacle avoidance and landing in unprepared sites (Ref. 6). The U.S. Army Aviation Development Directorate autonomy work in Refs. ...
... Manned and unmanned rotorcraft operating in unprepared locations must fly safely in the presence of unmapped obstacles and land safely in unprepared terrain. From full-size helicopters delivering cargo to military combat outposts to small unmanned aircraft surveying collapsed buildings, these vehicles must be able to (1) constantly asses the environment to respond to hazards, especially wires on their path; (2) navigate without GPS; and (3) reliably assess a potential landing zone's suitability for landing. This paper presents three technologies that address these needs and their use in the Office of Naval Research's Autonomous Aerial Cargo/Utility System 1 program: wire detection, GPS-free navigation, and landing zone (LZ) evaluation. ...
Rotorcraft operating in unprepared locations must be
capable of safe flight in the presence of unmapped
obstacles and absence of GPS, and must be able to
quickly and reliably assess a potential landing zone’s
suitability for landing. This paper presents technologies
that address these needs and the result of their application
to an actual unmanned helicopter prototype.
Autonomous flight of unmanned full‐size rotor‐craft has the potential to enable many new applications. However, the dynamics of these aircraft, prevailing wind conditions, the need to operate over a variety of speeds and stringent safety requirements make it difficult to generate safe plans for these systems. Prior work has shown results for only parts of the problem. Here we present the first comprehensive approach to planning safe trajectories for autonomous helicopters from takeoff to landing. Our approach is based on two key insights. First, we compose an approximate solution by cascading various modules that can efficiently solve different relaxations of the planning problem. Our framework invokes a long‐term route optimizer, which feeds a receding‐horizon planner which in turn feeds a high‐fidelity safety executive. Secondly, to deal with the diverse planning scenarios that may arise, we hedge our bets with an ensemble of planners. We use a data‐driven approach that maps a planning context to a diverse list of planning algorithms that maximize the likelihood of success. Our approach was extensively evaluated in simulation and in real‐world flight tests on three different helicopter systems for duration of more than 109 autonomous hours and 590 pilot‐in‐the‐loop hours. We provide an in‐depth analysis and discuss the various tradeoffs of decoupling the problem, using approximations and leveraging statistical techniques. We summarize the insights with the hope that it generalizes to other platforms and applications.
Express by micro aerial vehicle (MAV) becomes more and more popular because it can avoid the influence of terrain and save more space for taking-off and landing of aircraft. At present, quadrotor is often used in the express industry due to its flexibility and easy operation, and the flight trajectory plays an important role in the efficiency and safety level of express service. In this paper, the trajectory planning problem is studied for quadrotor delivering goods in urban environment with the purpose of avoiding the heavy ground traffic, and a cuckoo search (CS)-based trajectory planning method is proposed to solve the problem. First, a conceptual model containing all the key elements of the delivery task is developed, which presents a general idea of solving the problem. Some characteristics of the urban environment and the delivery task, such as the wind field, dense buildings and inclination of shipped goods, are taken into account in the trajectory planning model. The goal of the delivery task is to make the goods reach the destination accurately. When designing the CS-based trajectory planning algorithm, the basics of CS algorithm are explained, and then it is integrated into the trajectory planning problem. Comparative experiments are carried out to investigate the superiority of the proposed method, and the influences of parameters in CS algorithm are also discussed to conclude its performance in trajectory planning problem.
An improvement to autonomous Safe Landing Area Determination (SLAD) algorithms is proposed which takes into account aircraft motion and agility. This kinematic weight function is calculated over all points of the landing area and is based on current position, minimum hover position, and minimum time to hover. This paper presents the mathematical basis behind the kinematic weight function, its implementation in the Multi-Layer Surface Map Safe Landing Area Determination (MLSM-SLAD) as an additional layer, and simulation results of tests using a virtual UH-60 helicopter with a scanning LADAR terrain sensor. It is found that using the kinematic weight function reduces landing approach duration by over 18 seconds by eliminating overshoot of the landing point chosen from data scanned during the approach.
This paper describes the development and flight testing of an autonomous flight control system that allows for different levels of pilot interaction in both hover and forward flight. Three modes of operations are described, fully coupled autonomy, additive control, and piloted decoupled attitude-command. These modes are demonstrated on the Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) JUH-60A Black Hawk integrated with Obstacle Field Navigation (OFN) and Safe Landing Area Determination (SLAD) algorithms that both use a line scanning LADAR as their primary sensor. The paper will describe the control system, its performance, and demonstrate how it was used to transition into these modes while flying mission scenarios through mountainous terrain at speeds from hover to 100 kts.
