自主水下机器人实时避碰方法研究

自主水下机器人（AUV）要在复杂未知环境中自主作业，实时避碰是一种必不可少的自我保护能力。同时，能自动检测、识别、避开障碍也是AUV拥有“智能”的重要体现。因此，无论从实际应用前景还是从理论研究意义方面看，AUV实时避碰方法都具有重要的研究价值。 能使AUV像鱼儿一样自主地规避障碍一直是研究者追求的理想目标。但是，现有研究成果多倾向于AUV单个平面（水平面或垂直面）的避碰方法研究，而忽略了AUV是在三维空间运动的载体。在对现有AUV实时避碰方法进行深入分析和研究的基础上，本文提出了水平面和垂直面相结合的三维实时避碰方法，并针对以测距声纳为避碰传感器的一类远距离航行AUV，重点研究了三维避碰实现中的四个基本问题：一是如何从含有虚警的传感器原始数据中提取障碍信息；二是如何根据障碍信息决策规避行为；三是如何避免实时避碰行为陷入死循环或局部陷阱区域；四是如何评价和验证AUV实时避碰性能。 本文的主要研究内容及研究结论概述如下： 首先，针对测距声纳在实际应用中普遍存在的虚警和伪值问题，研究了基于D-S证据理论的数据融合方法。该方法包含4个部分：测距声纳模型、环境建模、一致性决策规则和证据融合。根据测距声纳和AUV的特殊性，本文分别提出了一种可根据载体航行速度和转动角度实时调整置信区域和基本可信度分配的测距声纳动态模型、基于灰数概念的一致性检验规则和基于确定性比例的冲突值分配方法。仿真和试验数据表明：基于D-S证据理论的数据融合方法比正则化方法、贝叶斯方法具有更高的检测概率和更低的漏检概率，能有效消除虚警信息、生成静态障碍环境的证据地图。 其次，从运动规划和路径规划两个层次研究了AUV三维实时避碰方法。在运动规划层，AUV要对视野内的障碍做出即时、准确的响应。这个响应包括改变航向、深/高度和降低航行速度。本文从多输入多输出模糊系统解耦设计的角度，将三维避碰行为分解为水平面和垂直面避碰行为，分别设计了2个双输入-单输出的模糊控制器；然后引入基于有限自动机的离散事件动态系统分析理论，建立了三维避碰过程有限自动机和基于事件反馈的监控器自动机；该自动机实现了水平面避碰行为、垂直面避碰行为、水平面和垂直面相结合的三维避碰行为之间的自主切换。 由于运动规划层的实时避碰行为存在“短视”的缺陷，要使AUV彻底摆脱当前障碍、逃离陷阱区域、避免出现死锁现象，需要在更高一级的路径规划层建立实时规划模块，负责根据离线地图和已获得的在线地图规划出远离障碍的优选路径。为此，本文研究了基于免疫遗传算法的实时路径规划方法。主要改进措施包括：提出以路径段数划分种群的小生境技术；采用细胞克隆和遗传操作并行搜索的策略；建立一组更适于AUV实时路径规划特殊性的适应性函数；利用疫苗接种机制改善抗体群质量。仿真实验表明：所提出的免疫遗传算法在收敛性能方面优于遗传算法和免疫算法，能满足AUV实时路径规划模块的要求，能实时产生避开复杂障碍的有效路径。 再次，本文第五章用上述测距声纳数据融合方法、模糊避碰规划方法、实时路径规划方法构建了AUV实时避碰系统，并在多功能半物理仿真平台上开展了仿真实验研究。多种典型单个和多个障碍场景的仿真实验全面演示、验证了AUV水平面、垂直面和三维的避碰能力，同时证明：基于事件反馈监控的模糊避碰规划方法能够引导AUV通过大部分复杂的未知障碍区域；基于免疫遗传算法的实时路径规划方法不仅能在线规划出远离障碍的优选路径，而且能帮助AUV逃离陷阱区域；所构建的AUV实时避碰系统能够实现AUV连续、稳定的三维实时避碰过程。另外，所提出的模糊避碰规划方法已在实际AUV上得到应用，并通过了湖上试验验证。 最后，研究了AUV实时避碰系统的评价和验证问题。共有三项成果：一是从系统工程角度创新性地提出实时避碰系统三维结构模型；二是建立一种AUV实时避碰能力综合评价体系，明确了单项和综合评价指标的组成因素；最后为评价和验证实时避碰系统，设计了多种典型障碍场景。 自主水下机器人实时避碰是一项极具挑战性的研究课题，本文只是针对一类欠驱动AUV、基于测距声纳研究了一种实时避碰系统的实现方法，并用仿真和试验验证了该系统的可行性和有效性。

仿象鼻并串联机构回避障碍“钻洞”的研究

研究了一种高冗余自由度并串联机构回避障碍的算法问题，并实现了运动仿真，核算法应用了优先顺位的理论，利用旋转张量法，对杆长随时间变化的高冗余自由度操作臂实现了变臂长的避障规划，并在ＣＡＤ工作站上完成了回避障碍钻洞的运动仿真，获得了满意的结果。国家自然科学基金

Navite: A Neural Network System For Sensory-Based Robot Navigation

A neural network system, NAVITE, for incremental trajectory generation and obstacle avoidance is presented. Unlike other approaches, the system is effective in unstructured environments. Multimodal inforrnation from visual and range data is used for obstacle detection and to eliminate uncertainty in the measurements. Optimal paths are computed without explicitly optimizing cost functions, therefore reducing computational expenses. Simulations of a planar mobile robot (including the dynamic characteristics of the plant) in obstacle-free and object avoidance trajectories are presented. The system can be extended to incorporate global map information into the local decision-making process.

A Kinect Based Indoor Navigation System for the Blind

Team NAVIGATE aims to create a robust, portable navigational aid for the blind. Our prototype uses depth data from the Microsoft Kinect to perform realtime obstacle avoidance in unfamiliar indoor environments. The device augments the white cane by performing two signi cant functions: detecting overhanging objects and identifying stairs. Based on interviews with blind individuals, we found a combined audio and haptic feedback system best for communicating environmental information. Our prototype uses vibration motors to indicate the presence of an obstacle and an auditory command to alert the user to stairs ahead. Through multiple trials with sighted and blind participants, the device was successful in detecting overhanging objects and approaching stairs. The device increased user competency and adaptability across all trials.

Developmental changes in the response to obstacles during prehension

Adults are proficient at reaching to grasp objects of interest in a cluttered workspace. The issue of concern, obstacle avoidance, was studied in 3 groups of young children aged 11-12, 9-10, and 7-8 years (n = 6 in each) and in 6 adults aged 18-24 years. Adults slowed their movements and decreased their maximum grip aperture when an obstacle was positioned close to a target object (the effect declined as the distance between target and obstacle increased). The children showed the same pattern, but the magnitude of the effect was quite different. In contrast to the adults, the obstacle continued to have a large effect when it was some distance from the target (and provided no physical obstruction to movement).

Echolocation signal structure in the Megachiropteran bat Rousettus aegyptiacus Geoffroy 1810

Rousettus aegyptiacus Geoffroy 1810 is a member of the only genus of Megachiropteran bats to use vocal echolocation, but the structure of its brief, click-like signal is poorly described. Although thought to have a simple echolocation system compared to that of Microchiroptera, R. aegyptiacus is capable of good obstacle avoidance using its impulse sonar. The energy content of the signal was at least an order of magnitude smaller than in Microchiropteran bats and dolphins (approximately 4 X 10(-8) J m(-2)). Measurement of the duration, amplitude and peak frequency demonstrate that the signals of this animal are broadly similar in structure and duration to those of dolphins. Gabor functions were used to model signals and to estimate signal parameters, and the quality of the Gabor function fit to the early part of the signal demonstrates that the echolocation signals of R. aegyptiacus match the minimum spectral spread for their duration and amplitude and are thus well matched to its best hearing sensitivity. However, the low energy content of the signals and short duration should make returning echoes difficult to detect. The performance of R. aegyptincus in obstacle avoidance experiments using echolocation therefore remains something of a conundrum.

Perception and software architecture for mobile robotics

When developing software for autonomous mobile robots, one has to inevitably tackle some kind of perception. Moreover, when dealing with agents that possess some level of reasoning for executing their actions, there is the need to model the environment and the robot internal state in a way that it represents the scenario in which the robot operates. Inserted in the ATRI group, part of the IEETA research unit at Aveiro University, this work uses two of the projects of the group as test bed, particularly in the scenario of robotic soccer with real robots. With the main objective of developing algorithms for sensor and information fusion that could be used e ectively on these teams, several state of the art approaches were studied, implemented and adapted to each of the robot types. Within the MSL RoboCup team CAMBADA, the main focus was the perception of ball and obstacles, with the creation of models capable of providing extended information so that the reasoning of the robot can be ever more e ective. To achieve it, several methodologies were analyzed, implemented, compared and improved. Concerning the ball, an analysis of ltering methodologies for stabilization of its position and estimation of its velocity was performed. Also, with the goal keeper in mind, work has been done to provide it with information of aerial balls. As for obstacles, a new de nition of the way they are perceived by the vision and the type of information provided was created, as well as a methodology for identifying which of the obstacles are team mates. Also, a tracking algorithm was developed, which ultimately assigned each of the obstacles a unique identi er. Associated with the improvement of the obstacles perception, a new algorithm of estimating reactive obstacle avoidance was created. In the context of the SPL RoboCup team Portuguese Team, besides the inevitable adaptation of many of the algorithms already developed for sensor and information fusion and considering that it was recently created, the objective was to create a sustainable software architecture that could be the base for future modular development. The software architecture created is based on a series of di erent processes and the means of communication among them. All processes were created or adapted for the new architecture and a base set of roles and behaviors was de ned during this work to achieve a base functional framework. In terms of perception, the main focus was to de ne a projection model and camera pose extraction that could provide information in metric coordinates. The second main objective was to adapt the CAMBADA localization algorithm to work on the NAO robots, considering all the limitations it presents when comparing to the MSL team, especially in terms of computational resources. A set of support tools were developed or improved in order to support the test and development in both teams. In general, the work developed during this thesis improved the performance of the teams during play and also the e ectiveness of the developers team when in development and test phases.

The SmartVision navigation prototype for the blind

The goal of the project "SmartVision: active vision for the blind" is to develop a small and portable but intelligent and reliable system for assisting the blind and visually impaired while navigating autonomously, both outdoor and indoor. In this paper we present an overview of the prototype, design issues, and its different modules which integrate a GIS with GPS, Wi-Fi, RFID tags and computer vision. The prototype addresses global navigation by following known landmarks, local navigation with path tracking and obstacle avoidance, and object recognition. The system does not replace the white cane, but extends it beyond its reach. The user-friendly interface consists of a 4-button hand-held box, a vibration actuator in the handle of the cane, and speech synthesis. A future version may also employ active RFID tags for marking navigation landmarks, and speech recognition may complement speech synthesis.

Manipulator trajectory planning using a MOEA

Generating manipulator trajectories considering multiple objectives and obstacle avoidance is a non-trivial optimization problem. In this paper a multi-objective genetic algorithm based technique is proposed to address this problem. Multiple criteria are optimized considering up to five simultaneous objectives. Simulation results are presented for robots with two and three degrees of freedom, considering two and five objectives optimization. A subsequent analysis of the spread and solutions distribution along the converged non-dominated Pareto front is carried out, in terms of the achieved diversity.

Field experiments for marine casualty detection with autonomous surface vehicles

In this paper we present a set of field tests for detection of human in the water with an unmanned surface vehicle using infrared and color cameras. These experiments aimed to contribute in the development of victim target tracking and obstacle avoidance for unmanned surface vehicles operating in marine search and rescue missions. This research is integrated in the work conducted in the European FP7 research project Icarus aiming to develop robotic tools for large scale rescue operations. The tests consisted in the use of the ROAZ unmanned surface vehicle equipped with a precision GPS system for localization and both visible spectrum and IR cameras to detect the target. In the experimental setup, the test human target was deployed in the water wearing a life vest and a diver suit (thus having lower temperature signature in the body except hands and head) and was equipped with a GPS logger. Multiple target approaches were performed in order to test the system with different sun incidence relative angles. The experimental setup, detection method and preliminary results from the field trials performed in the summer of 2013 in Sesimbra, Portugal and in La Spezia, Italy are also presented in this work.

Behaviours implemented using a vision system based on coded light projection

In a search for new sensor systems and new methods for underwater vehicle positioning based on visual observation, this paper presents a computer vision system based on coded light projection. 3D information is taken from an underwater scene. This information is used to test obstacle avoidance behaviour. In addition, the main ideas for achieving stabilisation of the vehicle in front of an object are presented

Predictive motion control of a mirosot mobile robot

This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obtained dynamic model, an integrated predictive control algorithm is proposed to position precisely with either stationary or moving obstacle avoidance. This objective is achieved automatically by introducing distant constraints into the open-loop optimization of control inputs. Simulation results demonstrate the feasibility of such control strategy for the deduced dynamic model

Multi-vehicle planning using RRT-connect

The problem of planning multiple vehicles deals with the design of an effective algorithm that can cause multiple autonomous vehicles on the road to communicate and generate a collaborative optimal travel plan. Our modelling of the problem considers vehicles to vary greatly in terms of both size and speed, which makes it suboptimal to have a faster vehicle follow a slower vehicle or for vehicles to drive with predefined speed lanes. It is essential to have a fast planning algorithm whilst still being probabilistically complete. The Rapidly Exploring Random Trees (RRT) algorithm developed and reported on here uses a problem specific coordination axis, a local optimization algorithm, priority based coordination, and a module for deciding travel speeds. Vehicles are assumed to remain in their current relative position laterally on the road unless otherwise instructed. Experimental results presented here show regular driving behaviours, namely vehicle following, overtaking, and complex obstacle avoidance. The ability to showcase complex behaviours in the absence of speed lanes is characteristic of the solution developed.

Motion planning of autonomous vehicles in a non-autonomous vehicle environment without speed lanes

Planning is one of the key problems for autonomous vehicles operating in road scenarios. Present planning algorithms operate with the assumption that traffic is organised in predefined speed lanes, which makes it impossible to allow autonomous vehicles in countries with unorganised traffic. Unorganised traffic is though capable of higher traffic bandwidths when constituting vehicles vary in their speed capabilities and sizes. Diverse vehicles in an unorganised exhibit unique driving behaviours which are analysed in this paper by a simulation study. The aim of the work reported here is to create a planning algorithm for mixed traffic consisting of both autonomous and non-autonomous vehicles without any inter-vehicle communication. The awareness (e.g. vision) of every vehicle is restricted to nearby vehicles only and a straight infinite road is assumed for decision making regarding navigation in the presence of multiple vehicles. Exhibited behaviours include obstacle avoidance, overtaking, giving way for vehicles to overtake from behind, vehicle following, adjusting the lateral lane position and so on. A conflict of plans is a major issue which will almost certainly arise in the absence of inter-vehicle communication. Hence each vehicle needs to continuously track other vehicles and rectify plans whenever a collision seems likely. Further it is observed here that driver aggression plays a vital role in overall traffic dynamics, hence this has also been factored in accordingly. This work is hence a step forward towards achieving autonomous vehicles in unorganised traffic, while similar effort would be required for planning problems such as intersections, mergers, diversions and other modules like localisation.

Planning autonomous vehicles in the absence of speed lanes using lateral potentials

Chaotic traffic, prevalent in many countries, is marked by a large number of vehicles driving with different speeds without following any predefined speed lanes. Such traffic rules out using any planning algorithm for these vehicles which is based upon the maintenance of speed lanes and lane changes. The absence of speed lanes may imply more bandwidth and easier overtaking in cases where vehicles vary considerably in both their size and speed. Inspired by the performance of artificial potential fields in the planning of mobile robots, we propose here lateral potentials as measures to enable vehicles to decide about their lateral positions on the road. Each vehicle is subjected to a potential from obstacles and vehicles in front, road boundaries, obstacles and vehicles to the side and higher speed vehicles to the rear. All these potentials are lateral and only govern steering the vehicle. A speed control mechanism is also used for longitudinal control of vehicle. The proposed system is shown to perform well for obstacle avoidance, vehicle following and overtaking behaviors.