A hyperbolic Lindstedt-Poincare method is presented to determine the homoclinic solutions of a kind of nonlinear oscillators, in which critical value of the homoclinic bifurcation parameter can be determined. The gene...A hyperbolic Lindstedt-Poincare method is presented to determine the homoclinic solutions of a kind of nonlinear oscillators, in which critical value of the homoclinic bifurcation parameter can be determined. The generalized Lienard oscillator is studied in detail, and the present method＇s predictions are compared with those of Runge-Kutta method to illustrate its accuracy.展开更多
This paper investigates the path-following control problem with obstacle avoidance of autonomous surface vehicles in the presence of actuator faults,uncertainty and external disturbances.Autonomous surface vehicles in...This paper investigates the path-following control problem with obstacle avoidance of autonomous surface vehicles in the presence of actuator faults,uncertainty and external disturbances.Autonomous surface vehicles inevitably suffer from actuator faults in complex sea environments,which may cause existing obstacle avoidance strategies to fail.To reduce the influence of actuator faults,an improved artificial potential function is constructed by introducing the lower bound of actuator efficiency factors.The nonlinear state observer,which only depends on measurable position information of the autonomous surface vehicle,is used to address uncertainties and external disturbances.By using a backstepping technique and adaptive mechanism,a path-following control strategy with obstacle avoidance and fault tolerance is designed which can ensure that the tracking errors converge to a small neighborhood of zero.Compared with existing results,the proposed control strategy has the capability of obstacle avoidance and fault tolerance simultaneously.Finally,the comparison results through simulations are given to verify the effectiveness of the proposed method.展开更多
快速识别和精准定位周围目标是自动驾驶车辆安全、自主行驶的前提和基础。针对基于体素的点云三维目标检测方法识别与定位不准的问题,提出一种基于改进SECOND算法的点云三维目标检测算法。首先,在二维卷积骨干网络中引入自适应的空间特...快速识别和精准定位周围目标是自动驾驶车辆安全、自主行驶的前提和基础。针对基于体素的点云三维目标检测方法识别与定位不准的问题,提出一种基于改进SECOND算法的点云三维目标检测算法。首先,在二维卷积骨干网络中引入自适应的空间特征融合模块融合不同尺度的空间特征,提高模型的特征表达能力。其次,充分利用边界框参数之间的关联性,采用three-dimensional distance-intersection over union (3D DIoU)损失作为边界框的定位回归损失函数,使得回归任务更加高效。最后,同时考虑候选框的分类置信度和定位精度,通过一个新的候选框质量评价标准,获得更平滑的回归结果。在KITTI测试集的实验结果表明,所提算法的3D检测精度优于许多以往的算法,与基准算法SECOND相比,在简单难度下的car类和cyclist类分别提高2.86百分点和3.84百分点,中等难度下分别提高2.99百分点和3.89百分点,困难难度下分别提高7.06百分点和4.27个百分点。展开更多
With the development of autonomous car,a vehicle is capable to sense its environment more precisely.That allows improved drving behavior decision strategy to be used for more safety and effectiveness in complex scenar...With the development of autonomous car,a vehicle is capable to sense its environment more precisely.That allows improved drving behavior decision strategy to be used for more safety and effectiveness in complex scenarios.In this paper,a decision making framework based on hierarchical state machine is proposed with a top-down structure of three-layer finite state machine decision system.The upper layer classifies the driving scenario based on relative position of the vehicle and its surrounding vehicles.The middle layer judges the optimal driving behavior according to the improved energy efficiency function targeted at multiple criteria including driving efficiency,safety and the grid-based lane vacancy rate.The lower layer constructs the state transition matrix combined with the calculation results of the previous layer to predict the optimal pass way in the region.The simulation results show that the proposed driving strategy can integrate multiple criteria to evaluate the energy efficiency value of vehicle behavior in real time,and realize the selection of optimal vehicle driving strategy.With popularity of automatic vehicles in future,the driving strategy can be used as a reference to provide assistance for human drive or even the real-time decision-making of autonomous driving.展开更多
基金supported by the National Natural Science Foundation of China (10672193)Sun Yat-sen University (Fu Lan Scholarship)the University of Hong Kong (CRGC grant).
文摘A hyperbolic Lindstedt-Poincare method is presented to determine the homoclinic solutions of a kind of nonlinear oscillators, in which critical value of the homoclinic bifurcation parameter can be determined. The generalized Lienard oscillator is studied in detail, and the present method＇s predictions are compared with those of Runge-Kutta method to illustrate its accuracy.
基金the National Natural Science Foundation of China(51939001,52171292,51979020,61976033)Dalian Outstanding Young Talents Program(2022RJ05)+1 种基金the Topnotch Young Talents Program of China(36261402)the Liaoning Revitalization Talents Program(XLYC20-07188)。
文摘This paper investigates the path-following control problem with obstacle avoidance of autonomous surface vehicles in the presence of actuator faults,uncertainty and external disturbances.Autonomous surface vehicles inevitably suffer from actuator faults in complex sea environments,which may cause existing obstacle avoidance strategies to fail.To reduce the influence of actuator faults,an improved artificial potential function is constructed by introducing the lower bound of actuator efficiency factors.The nonlinear state observer,which only depends on measurable position information of the autonomous surface vehicle,is used to address uncertainties and external disturbances.By using a backstepping technique and adaptive mechanism,a path-following control strategy with obstacle avoidance and fault tolerance is designed which can ensure that the tracking errors converge to a small neighborhood of zero.Compared with existing results,the proposed control strategy has the capability of obstacle avoidance and fault tolerance simultaneously.Finally,the comparison results through simulations are given to verify the effectiveness of the proposed method.
文摘快速识别和精准定位周围目标是自动驾驶车辆安全、自主行驶的前提和基础。针对基于体素的点云三维目标检测方法识别与定位不准的问题,提出一种基于改进SECOND算法的点云三维目标检测算法。首先,在二维卷积骨干网络中引入自适应的空间特征融合模块融合不同尺度的空间特征,提高模型的特征表达能力。其次,充分利用边界框参数之间的关联性,采用three-dimensional distance-intersection over union (3D DIoU)损失作为边界框的定位回归损失函数,使得回归任务更加高效。最后,同时考虑候选框的分类置信度和定位精度,通过一个新的候选框质量评价标准,获得更平滑的回归结果。在KITTI测试集的实验结果表明,所提算法的3D检测精度优于许多以往的算法,与基准算法SECOND相比,在简单难度下的car类和cyclist类分别提高2.86百分点和3.84百分点,中等难度下分别提高2.99百分点和3.89百分点,困难难度下分别提高7.06百分点和4.27个百分点。
基金This work was supported by the National Key Research and Development Program of China(2020YFB1600400)Key Research and Development Program of Shaanxi Province(2020GY-020)Supported by the Fundamental Research Funds for the Central Universities,CHD(300102320305).
文摘With the development of autonomous car,a vehicle is capable to sense its environment more precisely.That allows improved drving behavior decision strategy to be used for more safety and effectiveness in complex scenarios.In this paper,a decision making framework based on hierarchical state machine is proposed with a top-down structure of three-layer finite state machine decision system.The upper layer classifies the driving scenario based on relative position of the vehicle and its surrounding vehicles.The middle layer judges the optimal driving behavior according to the improved energy efficiency function targeted at multiple criteria including driving efficiency,safety and the grid-based lane vacancy rate.The lower layer constructs the state transition matrix combined with the calculation results of the previous layer to predict the optimal pass way in the region.The simulation results show that the proposed driving strategy can integrate multiple criteria to evaluate the energy efficiency value of vehicle behavior in real time,and realize the selection of optimal vehicle driving strategy.With popularity of automatic vehicles in future,the driving strategy can be used as a reference to provide assistance for human drive or even the real-time decision-making of autonomous driving.
