DEVELOPMENT OF A FRANGIBLE DESIGN OF SMALL FIXED-WING UNMANNED AERIAL SYSTEM

Existing studies show that small fixed-wing unmanned aircraft systems’ (FWUASs) mid-air collisions with aircraft can cause substantial damage. Upon a 250 knots impact, a ~1.8 kg “tractor” configuration of FW-UAS can perforate aircraft skin, thereby damaging the internal structures such as ribs, frames, etc., posing severe threat to manned air fleet. Significant damage is primarily caused by FW-UAS’s heavy and rigid components such as motor, battery, and payload especially due to their roughly in-line arrangement and proximity with one another. In this work, a modified FW-UAS finite element (FE) model was developed that included a “pusher” engine (i.e., motor in the aft of the forward fuselage) configuration to reduce the impact severity during airborne collisions. A polymeric foam nosecone was attached to the front of the FW-UAS FE model to dissipate impact energy. To assess its energy absorbing capacity, a comparative study with expanded polypropylene (EPP), polyurethane (PUR), and polystyrene (IMPAXX700) foams was performed. Conical and semi-spherical nosecone configurations were studied as part of this research. A series of LS-Dyna impact simulations were performed with the pusher configuration of FW-UAS impacting a 1.59 mm thick aluminum 2024-T3 flat plate sandwiched between a rigid target frame. In addition, a frangible design of the FW-UAS, in which the payload is diverged from the in-line collision trajectory of battery and motor upon impact, was implemented and assessed. Force generated during the initial stage of impact is leveraged through lightweight and friable structural links to diverge the payload to avoid impact along the single axis as of the battery and motor. Damage severity is evaluated through target plate tear, and velocity of payload during impact, it being the major damage causing component.

A comparison of two novel approaches for conducting detect and avoid flight test

This paper compares two approaches developed by the National Research Council of Canada to conduct ‘near-miss’ intercepts in flight test, and describes a new method for assessing the efficacy of these trajectories. Each approach used a different combination of flight test techniques and displays to provide guidance to the pilots to set-up the aircraft on a collision trajectory and to maintain the desired path. Approach 1 only provided visual guidance of the relative azimuth and position of the aircraft, whereas Approach 2 established the conflict point (latitude/longitude) from the desired geometry, and provided cross track error from the desired intercept as well as speed cueing for the arrival time. The performance of the approaches was analyzed by comparing the proportion of time where the predicted closest approach distance was below a desired threshold value. The analysis showed that Approach 2 resulted in more than double the amount of time spent at or below desired closest approach distance across all azimuths flown. Moreover, since less time was required to establish the required initial conditions, and to stabilize the flight paths, the authors were able to conduct 50% more intercepts.

Beam Search Algorithm for Anti-Collision Trajectory Planning for Many-to-Many Encounter Situations with Autonomous Surface Vehicles

A single anti-collision trajectory generation problem for an “own” vessel only is significantly different from the challenge of generating a whole set of safe trajectories for multi-surface vehicle encounter situations in the open sea. Effective solutions for such problems are needed these days, as we are entering the era of autonomous ships. The article specifies the problem of anti-collision trajectory planning in many-to-many encounter situations. The proposed original multi-surface vehicle beam search algorithm (MBSA), based on the beam search strategy, solves the problem. The general idea of the MBSA involves the application of a solution for one-to-many encounter situations (using the beam search algorithm, BSA), which was tested on real automated radar plotting aid (ARPA) and automatic identification system (AIS) data. The test results for the MBSA were from simulated data, which are discussed in the final part. The article specifies the problem of anti-collision trajectory planning in many-to-many encounter situations involving moving autonomous surface vehicles, excluding Collision Regulations (COLREGs) and vehicle dynamics.

Beam Search Algorithm for Ship Anti-Collision Trajectory Planning

The biggest challenges in the maritime environment are accidents and excessive fuel consumption. In order to improve the safety of navigation at sea and to reduce fuel consumption, the strategy of anti-collision, shortest trajectory planning is proposed. The strategy described in this paper is based on the beam search method. The beam search algorithm (BSA) takes into account many safe trajectories for the present ship and chooses the best in terms of length and other criteria. The risk of collision of present ship with any target ships is detected when the closest point of approach (CPA) of the present ship is violated by the target ship’s planned trajectory. Only course alteration of the present ship is applied, and not speed alteration. The algorithm has been implemented in the decision support system NAVDEC and tested in a real navigation environment on the m/f Wolin, a Polish ferry. Almost all BSA trajectories calculated were shorter in comparison to the standard NAVDEC-calculated algorithm.

A novel non-collision trajectory planning algorithm based on velocity potential field for robotic manipulator

This article presents a non-collision trajectory planning algorithm in three-dimensional space based on velocity potential field for robotic manipulators, which can be applied to collision avoidance among serial industrial robots and obstacles, and path optimization in multi-robot collaborative operation. The algorithm is achieved by planning joint velocities of manipulators based on attractive, repulsive, and tangential velocity of velocity potential field. To avoid oscillating at goal point, a saturated function is suggested to the attractive velocity potential field that slows down to the goal progressively. In repulsive velocity potential field, a spring damping system is designed to eliminate the chattering phenomenon near obstacles. Moreover, a fuzzy logic approach is used to optimize the spring damping coefficients for different velocities of manipulators. Different from the usual tangential velocity perpendicular to the repulsive velocity vector for avoiding the local minima problem, an innovative tangential velocity potential field is introduced that is considering the relative position and moving direction of obstacles for minimum avoidance path in three-dimensional space. In addition, a path priority strategy of collision avoidance is taken into account for better performance and higher efficiency when multi-robots cooperation is scheduled. The improvements for local minima and oscillation are verified by simulations in MATLAB. The adaptabilities of the algorithm in different velocities and priority strategies are demonstrated by simulations of two ABB robots in Robot Studio. The method is further implemented in an experimental platform with a SCARA and an ABB robot cooperation around a stationary obstacle and a moving object, and the result shows real time and effectiveness of the algorithms.

A Genetic Algorithm Based Approach for Pre-Collision Trajectory Optimization with Multi-Targets

Aiming at on-orbit capture task, a Genetic Algorithm based approach for pre-collision trajectory optimization with multi-targets is proposed in this paper. Through the analysis of task characteristics, multi-targets before collision are presented, which contain the point-to-point manoeuvre, impact pose control and impact impulse minimization. Genetic algorithm is employed to optimize the pre-collision trajectory after integrating multi-targets by setting task weight. At last, the simulation results verify the effectiveness of the proposed method.