A Survey of Collision Avoidance Methods for Unmanned Aircraft Systems

Threat detection and avoidance manoeuvres are complex fields of study. With the recent integration of Unmanned Aircraft Systems (UAS) in the airspace, Collision Avoidance (CA) methods have become a growing topic in Engineering. Commercial and large aircraft carry instrumentation onboard, such as Traffic Collision Avoidance System (TCAS), able to monitor in real-time the existence of threat and provide the most appropriate avoidance. However, this device in particular does not operate at any altitude below 1,000ft, also affecting general aviation. The lack of an onboard pilot is a challenge for unmanned systems that have to provide an equivalent level of safety as manned aircraft. This paper provides an overview of the Detect and Avoid (DAA) problem associated with the integration of UAS in the airspace; it aims to clarify misconceptions and other concepts. Special focus is given to CA methods since those techniques represent the avoidance procedure carried in the last stage before a collision and are particularly critical

Haptic Feedback Effects on Human Control of a UAV in a Remote Teleoperation Flight Task

The remote manual teleoperation of an unmanned aerial vehicle (UAV) by a human operator creates a human-in-the loop system that is of great concern. In a remote teleoperation task, a human pilot must make control decisions based upon sensory information provided by the governed system. Often, this information consists of limited visual feedback provided by onboard cameras that do not provide an operator with an accurate portrayal of their immediate surroundings compromising the safety of the mobile robot. Due to this shortfall, haptic force feedback is often provided to the human in an effort to increase their perceptual awareness of the surrounding world. To investigate the effects of this additional sensory information provided to the human op-erator, we consider two haptic force feedback strategies. They were designed to provide either an attractive force to influence control behavior towards a reference trajectory along a flight path, or a repulsive force directing operators away from obstacles to prevent collision. Subject tests were con-ducted where human operators manually operated a remote UAV through a corridor environment under the conditions of the two strategies. For comparison, the conditions of no haptic feedback and the liner combination of both attractive and repulsive strategies were included in the study. Experi-mental results dictate that haptic force feedback in general (including both attractive and repulsive force feedback) improves the average distance from surrounding obstacles up to 21%. Further statis-tical comparison of repulsive and attractive feedback modalities reveal that even though a repulsive strategy is based directly on obstacles, an attractive strategy towards a reference trajectory is more suitable across all performance metrics. To further examine the effects of haptic aides in a UAV teleoperation task, the behavior of the human system as part of the control loop was also investigated. Through a novel device placed on the end effector of the haptic device, human-haptic interaction forces were captured and further analyzed. With this information, system identification techniques were carried out to determine the plausibility of deriving a human control model for the system. By defining lateral motion as a one-dimensional compensatory tracking task the results show that general human control behavior can be identified where lead compensation in invoked to counteract second-order UAV dynamics

Shared-Control for the Kinematic and the Dynamic Models of a Mobile Robot

Abstract-This paper presents shared-control algorithms for the kinematic and the dynamic models of a mobile robot with a feasible configuration set defined by means of linear inequalities. The shared-control laws based on a hysteresis switch are designed in the case in which absolute positions are not available. Instead, we measure the distances to obstacles and angular differences. Formal properties of the closed-loop systems with the sharedcontrol are established by a Lyapunov-like analysis. Simulation results and experimental results are presented to show the effectiveness of the algorithm

Autonomous Collision Avoidance for a Teleoperated UAV Based on a Super-Ellipsoidal Potential Function

This thesis presents the design of a super-ellipsoidal potential function (SEPF) that can be used, in a static and dynamic environment, for autonomous collision avoidance of an unmanned aerial vehicle (UAV) in a 3-dimensional space. In the design of the SEPF, we have the full control over the shape and size of the potential function. In our proposed approach, a teleoperated UAV can not only autonomously avoid collision with surrounding objects but also track the operator\u27 control input as closely as possible. As a result, an operator can always be in control of the UAV for his/her high-level guidance and navigation task without worrying too much about the UAV collision avoidance while it is being teleoperated. The effectiveness of the proposed approach is demonstrated through a human-in-the-loop simulation using virtual robot experimentation platform (v-rep) and Matlab programs and experimentation using a physical quadrotor UAV in a laboratory environment

3D Obstacle Avoidance for Unmanned Autonomous System (UAS)

The goal of this thesis is to design a real-time, three-dimensional algorithm, named as the vector mesh (VM) algorithm, for unmanned aerial vehicles (UAV) to generate collision-free motion in indoor or outdoor environments with unknown obstacles. This promising technology can be utilized in both military and commercial applications. The VM approach employs three data reduction phases to compute optimal navigation directions while on-board scanning range sensor continuously updates depth data. In order to develop the VM, vector filed histogram (VFH) which applied in 2D space was first simulated in Matlab. Then a 2D autonomous navigation was implemented on a developed Vision-based Ground Vehicle (VGV) and the entire system was controlled by a modified VFH method which was computing in the Robot Operating System (ROS). Also, the VM algorithm was simulated in ROS and integrated into Gazebo simulator which is an effective graphic based robot simulator in complex indoor and outdoor environment. In this study, it has been shown that the proposed VM can be an effective 3D obstacle avoidance algorithm for typical small-UAVs if 3D information is continuously provided

A semi-autonomous UAV platform for indoor remote operation with visual and haptic feedback

International audienceWe present the development of a semi-autonomous quadrotor UAV platform for indoor teleoperation using RGB-D technology as exceroceptive sensor. The platform integrates IMU and Dense Visual Odometry pose estimation in order to stabilize the UAV velocity and track the desired velocity commanded by a remote operator though an haptic interface. While being commanded, the quadrotor autonomously performs a persistent pan-scanning of the surrounding area in order to extend the intrinsically limited field of view. The RGB-D sensor is used also for collision-safe navigation using a probabilistically updated local obstacle map. In the operator visual feedback, pan-scanning movement is real time compensated by an IMU-based adaptive filtering algorithm that lets the operator perform the drive experience in a oscillation-free frame. An additional sensory channel for the operator is provided by the haptic feedback, which is based on the obstacle map and velocity tracking error in order to convey information about the environment and quadrotor state. The effectiveness of the platform is validated by means of experiments performed without the aid of any external positioning system

The use of modern tools for modelling and simulation of UAV with Haptic

Unmanned Aerial Vehicle (UAV) is a research field in robotics which is in high demand in recent years, although there still exist many unanswered questions. In contrast, to the human operated aerial vehicles, it is still far less used to the fact that people are dubious about flying in or flying an unmanned vehicle. It is all about giving the control right to the computer (which is the Artificial Intelligence) for making decisions based on the situation like human do but this has not been easy to make people understand that it’s safe and to continue the enhancement on it. These days there are many types of UAVs available in the market for consumer use, for applications like photography to play games, to map routes, to monitor buildings, for security purposes and much more. Plus, these UAVs are also being widely used by the military for surveillance and for security reasons. One of the most commonly used consumer product is a quadcopter or quadrotor. The research carried out used modern tools (i.e., SolidWorks, Java Net Beans and MATLAB/Simulink) to model controls system for Quadcopter UAV with haptic control system to control the quadcopter in a virtual simulation environment and in real time environment. A mathematical model for the controlling the quadcopter in simulations and real time environments were introduced. Where, the design methodology for the quadcopter was defined. This methodology was then enhanced to develop a virtual simulation and real time environments for simulations and experiments. Furthermore, the haptic control was then implemented with designed control system to control the quadcopter in virtual simulation and real time experiments. By using the mathematical model of quadcopter, PID & PD control techniques were used to model the control setup for the quadcopter altitude and motion controls as work progressed. Firstly, the dynamic model is developed using a simple set of equations which evolves further by using complex control & mathematical model with precise function of actuators and aerodynamic coefficients Figure5-7. The presented results are satisfying and shows that flight experiments and simulations of the quadcopter control using haptics is a novel area of research which helps perform operations more successfully and give more control to the operator when operating in difficult environments. By using haptic accidents can be minimised and the functional performance of the operator and the UAV will be significantly enhanced. This concept and area of research of haptic control can be further developed accordingly to the needs of specific applications

The use of modern tools for modelling and simulation of UAV with Haptic

Unmanned Aerial Vehicle (UAV) is a research field in robotics which is in high demand in recent years, although there still exist many unanswered questions. In contrast, to the human operated aerial vehicles, it is still far less used to the fact that people are dubious about flying in or flying an unmanned vehicle. It is all about giving the control right to the computer (which is the Artificial Intelligence) for making decisions based on the situation like human do but this has not been easy to make people understand that it’s safe and to continue the enhancement on it. These days there are many types of UAVs available in the market for consumer use, for applications like photography to play games, to map routes, to monitor buildings, for security purposes and much more. Plus, these UAVs are also being widely used by the military for surveillance and for security reasons. One of the most commonly used consumer product is a quadcopter or quadrotor. The research carried out used modern tools (i.e., SolidWorks, Java Net Beans and MATLAB/Simulink) to model controls system for Quadcopter UAV with haptic control system to control the quadcopter in a virtual simulation environment and in real time environment. A mathematical model for the controlling the quadcopter in simulations and real time environments were introduced. Where, the design methodology for the quadcopter was defined. This methodology was then enhanced to develop a virtual simulation and real time environments for simulations and experiments. Furthermore, the haptic control was then implemented with designed control system to control the quadcopter in virtual simulation and real time experiments. By using the mathematical model of quadcopter, PID & PD control techniques were used to model the control setup for the quadcopter altitude and motion controls as work progressed. Firstly, the dynamic model is developed using a simple set of equations which evolves further by using complex control & mathematical model with precise function of actuators and aerodynamic coefficients Figure5-7. The presented results are satisfying and shows that flight experiments and simulations of the quadcopter control using haptics is a novel area of research which helps perform operations more successfully and give more control to the operator when operating in difficult environments. By using haptic accidents can be minimised and the functional performance of the operator and the UAV will be significantly enhanced. This concept and area of research of haptic control can be further developed accordingly to the needs of specific applications

Doctor of Philosophy

dissertationThis dissertation solves the collision avoidance problem for single- and multi-robot systems where dynamic effects are significant. In many robotic systems (e.g., highly maneuverable and agile unmanned aerial vehicles) the dynamics cannot be ignored and collision avoidance schemes based on kinematic models can result in collisions or provide limited performance, especially at high operating speeds. Herein, real-time, model-based collision avoidance algorithms that explicitly consider the robots' dynamics and perform real-time input changes to alter the trajectory and steer the robot away from potential collisions are developed, implemented, and verified in simulations and physical experiments. Such algorithms are critical in applications where a high degree of autonomy and performance are needed, for example in robot-assisted first response where aerial and/or mobile ground robots are required to maneuver quickly through cluttered and dangerous environments in search of survivors. Firstly, the research extends reciprocal collision avoidance to robots with dynamics by unifying previous approaches to reciprocal collision avoidance under a single, generalized representation using control obstacles. In fact, it is shown how velocity obstacles, acceleration velocity obstacles, continuous control obstacles, and linear quadratic regulator (LQR)-obstacles are special instances of the generalized framework. Furthermore, an extension of control obstacles to general reciprocal collision avoidance for nonlinear, nonhomogeneous systems where the robots may have different state spaces and different nonlinear equations of motion from one another is described. Both simulations and physical experiments are provided for a combination of differential-drive, differential-drive with a trailer, and car-like robots to demonstrate that the approach is capable of letting a nonhomogeneous group of robots with nonlinear equations of motion safely avoid collisions at real-time computation rates. Secondly, the research develops a stochastic collision avoidance algorithm for a tele-operated unmanned aerial vehicle (UAV) that considers uncertainty in the robot's dynamics model and the obstacles' position as measured from sensors. The model-based automatic collision avoidance algorithm is implemented on a custom-designed quadcopter UAV system with on-board computation and the sensor data are processed using a split-and-merge segmentation algorithm and an approximate Minkowski difference. Flight tests are conducted to validate the algorithm's capabilities for providing tele-operated collision-free operation. Finally, a set of human subject studies are performed to quantitatively compare the performance between the model-based algorithm, the basic risk field algorithm (a variant on potential field), and full manual control. The results show that the model-based algorithm performs significantly better than manual control in both the number of collisions and the UAV's average speed, both of which are extremely vital, for example, for UAV-assisted search and rescue applications. Compared to the potential-field-based algorithm, the model-based algorithm allowed the pilot to operate the UAV with higher average speeds

Development, analysis, and implications of open-source simulations of remotely piloted aircraft

In recent years, the use of Remotely Piloted Aircraft (RPAs) for diverse purposes has increased exponentially. As a consequence, the uncertainty created by situations turning into a threat for civilians has led to more restrictive regulations from national administrations such as Transport Canada. Their purpose is to safely integrate RPAs in the current airspace used for piloted aviation by evaluating Sense and Avoid (SAA) strategies and close encounters. The difficulty falls on having to rely on simulated environments because of the risk to the human pilot in the piloted aircraft. In the first part of this research, the technical difficulties associated with the development and study of RPA computer models are discussed. It explores the rationale behind using Open-Source Software (OSS) platforms for simulating RPAs as well as the challenges associated with interacting with OSS at graduate student level. A set of recommendations is proposed as the solution to improve the graduate student experience with OSS. In the second part, particular challenges related to the design of OSS computer models are addressed. Based on: (1) the differences and similarities between piloted and RPA flight simulators and (2) existing Verification and Validation (V&V) approaches, a validation method is presented as a solution to the subject of developing fixed-wing RPAs in OSS environments. This method is used to design two flight dynamics models with SAA applications. The first computer model is presented in tutorial format as a case study for the validation procedure whereas the second computer model is specific for testing SAA strategies. In the last part, one of the designed RPAs is integrated into a computer environment with a representative general aircraft. From the simulated encounters, a diving avoidance manoeuvre on the RPA is developed. This performance is observed to analyze the consequences to the airspace. The implications of this research are seen from three perspectives: (1) the OSS challenges in graduate school are wide-spread across disciplines, (2) the proposed validation procedure is adaptable to fit any computer model and simulation scenario, and (3) the simulated OSS framework with an RPA computer model has served for testing preliminary SAA methods with close encounters with manned aircraft