SIA OpenIR  > 机器人学研究室
Alternative TitleResearch on 3D Unstructured Environment Modeling and Unmmaned Aerial Vehicle Motion Planning
Keyword飞行机器人 非结构环境建模 在线位姿估计 路径规划 运动规划
Degree Discipline模式识别与智能系统
Degree Name博士
Degree Grantor中国科学院沈阳自动化研究所
Place of Conferral沈阳
Abstract本文主要结合飞行机器人的感知和自主决策开展如下研究。非结构化的环境感知和表达问题:首先问题在于感知,无人机高速的响应特点决定了其环境感知对现有的方法提出了更高的挑战,同时,非结构环境的非一般性描述和时变特点也使得传统的建模方法在此环境下失效。为了更加快速感知环境,本文提出了基于回路检测补偿的方法来实现高速感知。基于RGB-D SLAM,本文提出了离散高斯模型建模方法来表征非结构环境。飞行机器人的轨迹和运动规划:飞行机器人的要求更快的规划响应来完成对于动态环境的适应,并且随着环境越来越复杂,无人机的运动规划空间通常面临着要处理大量的障碍物。这样往往需要算法进行及其繁杂的障碍物碰撞和安全区域监测,传统算法对于非结构窄通道环境规划的处理非常耗时。本文突破性的提出了基于环境信息诱导随机采样算法,结合障碍物和目标的双重信息诱导,使得算法可以在窄通道区域有效的产生路径联系以完成快速路径规划。同时本文还提出了基于六阶贝塞尔曲线生成控制平滑的运动轨迹,使得飞行机器人可以以最小能量和危险系数进行在线导航。飞行机器人的在线突发威胁决策:对于机器人来说,动态障碍的建模和规避一直以来是研究的难点,特别是在进行高机动运动的时候,这时需要导航规划器具有非常快的响应速度和预测规避的能力。本文首次解决了随机搜索树的多路径搜索问题,并且提出了基于对路径规划实现快速机动避障。这一方法被实验证明比传统的重规划方向具有更好的时效,而且,还能够动态的返回之前的轨迹来规避逆向运动障碍物的问题。本文最后针对研究的成果和不足对论文进行了总结,并且对后续可能进行的研究方向和验证方法进行了简要陈述。
Other AbstractThis paper mainly combines the perception and decision-making of aerial robots to carry out the following research. Unstructured environment perception and modeling problems: The first problem is perception. The high-speed response characteristics of drones determine that their environmental perception poses a higher challenge to existing methods. At the same time, the non-conformity of non-structural environments description and time-varying features also make traditional modeling methods fail in this environment. In order to perceive the environment more quickly, this paper proposes a method based on loop detection compensation to achieve high-speed sensing. Based on perception, this paper proposes a discrete Gaussian model modeling method to characterize the non-structural environment. The path planning and motion planning of the aerial robot: Aerial robot requires a faster planning response to complete the adaptation to the dynamic environment, and as the environment becomes more complex, the motion planning space of the drone is usually faced with dealing with a large number of obstacles. This often requires algorithms to be able to perform computationally obstacle collision detection and safe area monitoring. The traditional algorithm is very time-consuming for the processing of unstructured narrow channel environments. This paper proposes a random sampling algorithm based on environmental information, combined with the dual information induction from obstacles and targets so that the algorithm can effectively generate path links in narrow channel areas to complete fast path planning. At the same time, this paper also proposes to control the smoothing motion trajectory based on the sixth-order Bezier curve, so that the flying robot can conduct online navigation with minimum energy and risk coefficient. Online dynamic threat avoidance of aerial robots: For robots, the modeling and avoidance of dynamic obstacles is one of the difficult points, especially when performing high maneuvering movements. Especially, if the navigation planner needs a very fast response. it requires the planner to have a high speed and predictive ability to evade. This paper solves the multi-path search problem of a random search tree for the first time and proposes a fast maneuver obstacle avoidance based on path planning. This method has been experimentally proven to have better timeliness than the traditional re-planning direction, and it is also possible to dynamically return to the previous trajectory to avoid the problem of reverse motion obstacles. Finally, in the conclusion and prospects, the research on the thesis is summarized, and the possible future research directions are briefly stated.
Contribution Rank1
Document Type学位论文
Recommended Citation
GB/T 7714
杨亮. 非结构环境三维建模及飞行机器人运动规划研究[D]. 沈阳. 中国科学院沈阳自动化研究所,2019.
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