Vision‐based navigation through urban canyons

We address the problem of navigating unmanned vehicles safely through urban canyons in two dimensions using only vision‐based techniques. Two commonly used vision‐based obstacle avoidance techniques (namely stereo vision and optic flow) are implemented on an aerial and a ground‐based robotic platform and evaluated for urban canyon navigation. Optic flow is evaluated for its ability to produce a centering response between obstacles, and stereo vision is evaluated for detecting obstacles to the front. We also evaluate a combination of these two techniques, which allows a vehicle to detect obstacles to the front while remaining centered between obstacles to the side. Through experiments on an unmanned ground vehicle and in simulation, this combination is shown to be beneficial for navigating urban canyons, including T‐junctions and 90‐deg bends. Experiments on a rotorcraft unmanned aerial vehicle, which was constrained to two‐dimensional flight, demonstrate that stereo vision allowed it to detect an obstacle to the front, and optic flow allowed it to turn away from obstacles to the side. We discuss the theory behind these techniques, our experience in implementing them on the robotic platforms, and their suitability to the urban canyon navigation problem. © 2009 Wiley Periodicals, Inc.     

Design,control, and visual navigation of the DelftaCopter VTOL tail‐sitter UAV

To participate in the Outback Medical Express UAV Challenge 2016, a vehicle was designed and tested that can autonomously hover precisely, takeoff and land vertically, fly fast forward efficiently, and use computer vision to locate a person and a suitable landing location. The vehicle is a novel hybrid tail‐sitter combining a delta‐shaped biplane fixed‐wing and a conventional helicopter rotor. The rotor and wing are mounted perpendicularly to each other,and the entire vehicle pitches down to transition from hover to fast forward flight where the rotor serves as propulsion. To deliver sufficient thrust in hover while still being efficient in fast forward flight, a custom rotor system was designed. The theoretical design was validated with energy measurements, wind tunnel tests, and application in real‐world missions. A rotor‐head and corresponding control algorithm were developed to allow transitioning flight with the nonconventional rotor dynamics that are caused by the fuselage rotor interaction. Dedicated electronics were designed that meet vehicle needs and comply with regulations to allow safe flight beyond visual line of sight. Vision‐based search and guidance algorithms running on a stereo‐vision fish‐eye camera were developed and tested to locate a person in cluttered terrain never seen before. Flight tests and a competition participation illustrate the applicability of the DelftaCopter concept.     

High performance and safe flight of full‐scale helicopters from takeoff to landing with an ensemble of planners

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.     

Improved nonlinear trajectory tracking using RBFNN for a robotic helicopter

This paper presents a backstepping control method using radial‐basis‐function neural network (RBFNN) for improving trajectory tracking performance of a robotic helicopter. Many well‐known nonlinear controllers for robotic helicopters have been constructed based on the approximate dynamic model in which the coupling effect is neglected; their qualitative behavior must be further analyzed to ensure that the unmodeled dynamics do not destroy the stability of the closed‐loop system. In order to improve the controller design process, the proposed controller is developed based on the complete dynamic model of robotic helicopters by using an RBFNN function approximation to the neglected dynamic uncertainties, and then proving that all the trajectory tracking error variables are globally ultimately bounded and converge to a neighborhood of the origin. The merits of the proposal controller are exemplified by four numerical simulations, showing that the proposed controller outperforms a well‐known controller in (J. Robust Nonlinear Control 2004; 14 (12):1035–1059). Copyright © 2009 John Wiley & Sons, Ltd.     

Vertical manoeuvring and rotor speed robust control for mini-helicopter

A robust control approach is presented for vertical manoeuvring helicopters with aerodynamics acting on the main rotor. An induced inflow observer is applied which only requires the measured values of the vertical accelerator in the body frame. The controller consists of three parts: a feedback linearisation controller, a nominal controller and a robust compensator. Feedback linearisation is applied to decouple the vertical motion dynamics and the rotor speed dynamics; the nominal controller aims to achieve desired performances for the nominal system without external disturbances or uncertainties; and the robust compensator is designed to restrain the effect of the external disturbance and the uncertainties. It is proven that all the states involved are bounded and the tracking error of the actual system can converge into an arbitrary specified boundary in a finite time for any given initial state. The results of outdoor flight experiments show that the robust tracking performances are consistent with the theory analysis conclusions.     

基于人工势场的机器人遥操作安全预警域动态生成方法

为了避免机器人遥操作过程中,机器人与环境物体不必要的碰撞,以及解决"运动-等待"现象影响机器人系统安全性和效率的问题,提出了基于人工势场生成动态安全预警域的算法.该算法根据等势面原理生成的预警域既可以实时地检测机器人与环境物体的距离,又可以根据机器人的速度和加速度划定一个相对安全的区域,避免机器人在下一时刻因为速度过快与环境物体发生碰撞.最后搭建遥操作实验平台,进行了机器人在预警算法的辅助下快速抓取目标的实验.实验证明,该算法可有效提高远程机器人遥操作的安全性和效率.     

Autonomous landing at unprepared sites by a full-scale helicopter

Helicopters are valuable since they can land at unprepared sites; however, current unmanned helicopters are unable to select or validate landing zones (LZs) and approach paths. For operation in unknown terrain it is necessary to assess the safety of a LZ. In this paper, we describe a lidar-based perception system that enables a full-scale autonomous helicopter to identify and land in previously unmapped terrain with no human input.We describe the problem, real-time algorithms, perception hardware, and results. Our approach has extended the state of the art in terrain assessment by incorporating not only plane fitting, but by also considering factors such as terrain/skid interaction, rotor and tail clearance, wind direction, clear approach/abort paths, and ground paths.In results from urban and natural environments we were able to successfully classify LZs from point cloud maps. We also present results from 8 successful landing experiments with varying ground clutter and approach directions. The helicopter selected its own landing site, approaches, and then proceeds to land. To our knowledge, these experiments were the first demonstration of a full-scale autonomous helicopter that selected its own landing zones and landed.     

飞行数据驱动的共轴式直升机姿态显示设计

基于飞行参数记录仪的记录数据对飞机空中飞行状态进行重现,是实施飞行操控质量监控的重要手段。该文结合VisualC 和OpenGL技术,给出了一种以已译码飞行数据作为驱动的共轴式直升机三维飞行姿态计算机仿真的有效方法,直观重现了飞机的飞行姿态及其它状态相关数据,为直升机的飞行安全监控和飞行员日常训练提供可靠依据。     

New Traversability Indices and Traversability Grid for Integrated Sensor/Map‐Based Navigation

This paper presents new measures of terrain traversability at short range and long range of a mobile robot; namely, local and global traversability indices. The sensor‐based local traversability index is related by a set of linguistic rules to large obstacles and surface softness within a short range of the robot measured by on‐board sensors. The map‐based global traversability index is obtained from the terrain topographic map, and is based on major surface features such as hills and lakes within a long range of the robot. These traversability indices complement the mid‐range sensor‐based regional traversability index introduced earlier. Each traversability index is represented by four fuzzy sets with the linguistic labels {POOR, LOW, MODERATE, HIGH}, corresponding to surfaces that are unsafe, moderately‐unsafe, moderately‐safe, and safe for traversal, respectively. The global terrain analysis also leads to the new concepts of traversability map and traversability grid for representation of terrain quality based on the global map information. The traversability indices are used in two sensor‐based traverse‐local and traverse‐regional behaviors and one map‐based traverse‐global behavior. These behaviors are integrated with a map‐based seek‐goal behavior to ensure that the mobile robot reaches its goal safely while avoiding both sensed and mapped terrain hazards. This provides a unified system in which the two independent sources of terrain quality information, i.e., prior maps and on‐board sensors, are integrated together for reactive robot navigation. The paper is concluded by a graphical simulation study. © 2003 Wiley Periodicals, Inc.     

Predictive Guidance-Based Navigation for Mobile Robots: A Novel Strategy for Target Interception on Realistic Terrains

This paper presents a novel online trajectory planning method for the autonomous robotic interception of mobile targets in the presence of dynamic obstacles. The objective is time-optimal position and velocity matching (also referred to as rendezvous) while traversing realistic terrains with uneven topologies. The primary novelty of the proposed interception method lies in its ability to minimize rendezvous time with the target, as well as energy consumption, by directly considering the dynamics of the obstacles and the target while accurately determining a feasible way to travel through the realistic terrain. This objective is achieved by computing rendezvous maneuvers using an advanced predictive guidance law. The method is designed to effectively cope with maneuvering targets/obstacles by predicting their future velocities and accelerations. Obstacle avoidance and terrain navigation are seamlessly integrated. Extensive simulation and experimental analyses, some of which are reported in this paper, have clearly demonstrated the time efficiency of the proposed rendezvous method.     

Development of a novel crawler mechanism with polymorphic locomotion

The design of a novel crawler mechanism with polymorphic locomotion is presented in this paper. The proposed mechanism, which is equipped with a planetary gear reducer, provides two kinds of outputs in different form only using one actuator. By determining the reduction ratio of two outputs in a suitable proportion, the crawler mechanism is capable of switching between two locomotion modes autonomously according to terrain. Using this property, robots equipped with the crawler mechanism can perform more efficient and adaptable locomotion or posture in irregular environments. Experimental tests showed that the developed crawler-driven module equipped with the proposed crawler mechanism cannot only move on moderately rugged terrain, but also perform a particular locomotion mode to negotiate high obstacles or adapt to different terrains without any sensors for distinguishing obstacles or any extra actuators or mechanisms for assistance.     

Vision-based obstacle detection for rotorcraft flight

The ability of rotorcraft to fly at low altitude is hindered by the high pilot workload required to avoid obstacles. The development of automation tools that can detect obstacles in the rotorcraft flight path, warn the crew, and interact with the guidance system to avoid detected obstacles would significantly reduce pilot workload and increase safety. This article describes an obstacle detection approach based on feature tracking and recursive range estimation that takes into account the characteristics of rotorcraft flight. The merits and weaknesses of the approach are discussed using image sequences from the laboratory and from flight. © 1992 John Wiley & Sons, Inc.     

某型直升机飞行性能仿真建模与验证

主要研究并建立直升机飞行性能仿真模型,在直升机动力学和运动学微分方程的基础上重点解算作用在直升机各部件上的气动力和力矩模型,建立旋翼和尾桨的气动仿真模型,对旋翼挥舞运动进行了分析研究,还考虑了平尾、垂尾、机身和重力的仿真模型。最后通过对各飞行性能指标及其验证原理方法的分析研究,验证了静态性能指标,应用标量指标法验证动态性能指标。     

Continuous‐Time Three‐Dimensional Mapping for Micro Aerial Vehicles with a Passively Actuated Rotating Laser Scanner

The ability to generate accurate and detailed three‐dimensional (3D) maps of a scene from a mobile platform is an essential technology for a wide variety of applications from robotic navigation to geological surveying. In many instances, the best vantage point is from above, and as a result, there is a growing demand for low‐altitude mapping solutions from micro aerial vehicles such as small quadcopters. Existing lidar‐based 3D airborne mapping solutions rely on GPS/INS solutions for positioning, or focus on producing relatively low‐fidelity or locally focused maps for the purposes of autonomous navigation. We have developed a general‐purpose airborne 3D mapping system capable of continuously scanning the environment during flight to produce accurate and dense point clouds without the need for a separate positioning system. A key feature of the system is a novel passively driven mechanism to rotate a lightweight 2D laser scanner using the rotor downdraft from a quadcopter. The data generated from the spinning laser is input into a continuous‐time simultaneous localization and mapping (SLAM) solution to produce an accurate 6 degree‐of‐freedom trajectory estimate and a 3D point cloud map. Extensive results are presented illustrating the versatility of the platform in a variety of environments including forests, caves, mines, heritage sites, and industrial facilities. Comparison with conventional surveying methods and equipment demonstrates the high accuracy and precision of the proposed solution.     

Towards Autonomous Autorotation Landing for Small Size Unmanned Helicopters

The consideration of safety issues in the operation of helicopters involves the capability to perform emergency descending maneuvers through the autorotation principle when the engine is no longer supplying power. When comparing manned and unmanned helicopters, the lower rotor inertia of UAV configurations makes this functionality even more challenging for the pilot since more accurate timing and speed control of the flare phase are required. This paper presents a complete set of guidelines to design a controller for the autonomous autorotation landing of an UAV. This analysis is based on experimental data that corresponds to autorotation landings of a small-size helicopter carried out by a skillful pilot.     

Design and implementation of a leader-follower cooperative control system for unmanned helicopters

In this paper, we present a full scheme for the cooperative control of multiple unmanned aerial vehicle (UAV) helicopters. We adopt the leader-follower pattern to maintain a fixed geometrical formation while navigating the UAVs following certain trajectories. More specifically, the leader is commanded to fly on some predefined trajectories, and each follower is controlled to maintain its position in formation using the measurement of its inertial position and the information of the leader position and velocity, obtained through a wireless modem. More specifications are made for multiple UAV formation flight. In order to avoid possible collisions of UAV helicopters in the actual formation flight test, a collision avoidance scheme based on some predefined alert zones and protected zones is employed. Simulations and experimental results are presented to verify our design.     

Autonomous Autorotation of Unmanned Rotorcraft using Nonlinear Model Predictive Control

Safe operations of unmanned rotorcraft hinge on successfully accommodating failures during flight, either via control reconfiguration or by terminating flight early in a controlled manner. This paper focuses on autorotation, a common maneuver used to bring helicopters safely to the ground even in the case of loss of power to the main rotor. A novel nonlinear model predictive controller augmented with a recurrent neural network is presented that is capable of performing an autonomous autorotation. Main advantages of the proposed approach are on-line, real-time trajectory optimization and reduced hardware requirements.     

Intuitive 3D Maps for MAV Terrain Exploration and Obstacle Avoidance

Recent development showed that Micro Aerial Vehicles (MAVs) are nowadays capable of autonomously take off at one point and land at another using only one single camera as exteroceptive sensor. During the flight and landing phase the MAV and user have, however, little knowledge about the whole terrain and potential obstacles. In this paper we show a new solution for a real-time dense 3D terrain reconstruction. This can be used for efficient unmanned MAV terrain exploration and yields a solid base for standard autonomous obstacle avoidance algorithms and path planners. Our approach is based on a textured 3D mesh on sparse 3D point features of the scene. We use the same feature points to localize and control the vehicle in the 3D space as we do for building the 3D terrain reconstruction mesh. This enables us to reconstruct the terrain without significant additional cost and thus in real-time. Experiments show that the MAV is easily guided through an unknown, GPS denied environment. Obstacles are recognized in the iteratively built 3D terrain reconstruction and are thus well avoided.     

新型无人直升机纵横向无姿态反馈自适应控制

针对小型无人直升机固有的多轴多齿轮啮合复杂传动系统存在的非线性振动所引起的姿态测量低可靠性问题,以新型涵道风扇式无人直升机为例,提出了一种纵横向无姿态反馈的自适应控制策略.增稳回路采用模型参考自适应解耦控制,加速度回路采用自适应极点配置,位移回路采用主导极点可配置的PD控制,实现了自动航线飞行.试飞实验表明,在飞行速度变化较为显著时,偏航距较小,达到了满意的控制效果,可为无人直升机姿态传感器故障应对提供参考.     

Control of distributed autonomous robotic systems using principlesof pattern formation in nature and pedestrian behavior

Self-organized and error-resistant control of distributed autonomous robotic units in a manufacturing environment with obstacles where the robotic units have to be assigned to manufacturing targets in a cost effective way, is achieved by using two fundamental principles of nature. First, the selection behavior of modes is used which appears in pattern formation of physical, chemical and biological systems. Coupled selection equations based on these pattern formation principles can be used as dynamical system approach to assignment problems. These differential equations guarantee feasibility of the obtained solutions which is of great importance in industrial applications. Second, a model of behavioral forces is used, which has been successfully applied to describe self-organized crowd behavior of pedestrians. This novel approach includes collision avoidance as well as error resistivity. In particular, in systems where failures are of concern, the suggested approach outperforms conventional methods in covering up for sudden external changes like breakdowns of some robotic units. The capability of this system is demonstrated in computer simulations.