针对仿人机器人攀爬的实时运动生成问题,提出一种基于非线性模型预测控制(nonlinear model predictive control,NMPC)方法,能够综合优化路径和肢体运动。该方法将攀爬任务视为一个机械约束的NMPC问题,并使用了基于墙体图的状态相关权重...针对仿人机器人攀爬的实时运动生成问题,提出一种基于非线性模型预测控制(nonlinear model predictive control,NMPC)方法,能够综合优化路径和肢体运动。该方法将攀爬任务视为一个机械约束的NMPC问题,并使用了基于墙体图的状态相关权重和势函数。在每个采样时间点根据墙体信息和机器人的状态进行计算获得控制输入。此外,还提出了为NMPC在线配置性能指标的视距评估方法。研究结果表明:随着视距的减小,控制输入的计算时间也随之减少,有效降低了计算成本;与将墙体上的所有支撑都纳入视距范围的情况相比,攀爬时间最多能减少36.4%,有效适应了复杂的墙体模型。展开更多
In order to satisfy the requirement of realtime gait programming of humanoid walking with foot rotation,a kind of modified Nonlinear Model Predictive Control (NMPC) scheme was proposed. Based on setting suitable kinet...In order to satisfy the requirement of realtime gait programming of humanoid walking with foot rotation,a kind of modified Nonlinear Model Predictive Control (NMPC) scheme was proposed. Based on setting suitable kinetic and kinematic virtual constraints of Single Support Phase (SSP) and three subphases of Double Support Phase (DSP) ,complex realtime gait programming problem was simplified to four online NMPC dynamic optimization problems. A numerical approach was proposed to transform the dynamical optimization problem to the finite dimensional static optimization problem which can be solved by Sequential Quadratic Programming (SQP) . It can be concluded from simulation that using this method on BIP model can realize online gait programming of dynamic walking with foot rotation and the biped stability can be satisfied such that there is no sliding during walking.展开更多
To address the problem of instability and inaccuracy when the Unmanned Aerial Vehicles(UAVs) formation equipped with bearing-only sensor network tracks a maneuvering target,this paper proposes a distributed cooperativ...To address the problem of instability and inaccuracy when the Unmanned Aerial Vehicles(UAVs) formation equipped with bearing-only sensor network tracks a maneuvering target,this paper proposes a distributed cooperative tracking control method considering the effectiveness of passive detection. First, the system model of passive detection in UAV formation is constructed.Then, the Geometric Dilution of Precision(GDOP) of bearing-only sensor nodes pair on the observation plane is analyzed. Building on this foundation, the pairwise form is expanded to obtain the optimal geometric configuration for the entire network. Subsequently, the Distributed Cubature Information Filtering(DCIF) is integrated with the weighted average consensus protocol to design the distributed cooperative observer suitable for the system model, enabling state estimation of the target. Finally, within the distributed architecture, the Nonlinear Model Predictive Controller(NMPC) is designed. This controller autonomously assembles the UAV formation during the assembly phase and forms an optimal detection array. The UAV formation then tracks the target using the virtual geometric center based on the established rigid geometric configuration. The simulation experiments validate that the proposed model and method can enhance the passive detection effectiveness of the UAV formation, thereby achieving stable and efficient distributed cooperative tracking for the maneuvering target.展开更多
文摘针对仿人机器人攀爬的实时运动生成问题,提出一种基于非线性模型预测控制(nonlinear model predictive control,NMPC)方法,能够综合优化路径和肢体运动。该方法将攀爬任务视为一个机械约束的NMPC问题,并使用了基于墙体图的状态相关权重和势函数。在每个采样时间点根据墙体信息和机器人的状态进行计算获得控制输入。此外,还提出了为NMPC在线配置性能指标的视距评估方法。研究结果表明:随着视距的减小,控制输入的计算时间也随之减少,有效降低了计算成本;与将墙体上的所有支撑都纳入视距范围的情况相比,攀爬时间最多能减少36.4%,有效适应了复杂的墙体模型。
基金Sponsored by the National High Technology Research and Development Program of China ( 863 Program) ( Grant No. 2006AA04Z201)
文摘In order to satisfy the requirement of realtime gait programming of humanoid walking with foot rotation,a kind of modified Nonlinear Model Predictive Control (NMPC) scheme was proposed. Based on setting suitable kinetic and kinematic virtual constraints of Single Support Phase (SSP) and three subphases of Double Support Phase (DSP) ,complex realtime gait programming problem was simplified to four online NMPC dynamic optimization problems. A numerical approach was proposed to transform the dynamical optimization problem to the finite dimensional static optimization problem which can be solved by Sequential Quadratic Programming (SQP) . It can be concluded from simulation that using this method on BIP model can realize online gait programming of dynamic walking with foot rotation and the biped stability can be satisfied such that there is no sliding during walking.
基金supported by the National Natural Science Foundation of China (Nos. 62176214 and 61973253)。
文摘To address the problem of instability and inaccuracy when the Unmanned Aerial Vehicles(UAVs) formation equipped with bearing-only sensor network tracks a maneuvering target,this paper proposes a distributed cooperative tracking control method considering the effectiveness of passive detection. First, the system model of passive detection in UAV formation is constructed.Then, the Geometric Dilution of Precision(GDOP) of bearing-only sensor nodes pair on the observation plane is analyzed. Building on this foundation, the pairwise form is expanded to obtain the optimal geometric configuration for the entire network. Subsequently, the Distributed Cubature Information Filtering(DCIF) is integrated with the weighted average consensus protocol to design the distributed cooperative observer suitable for the system model, enabling state estimation of the target. Finally, within the distributed architecture, the Nonlinear Model Predictive Controller(NMPC) is designed. This controller autonomously assembles the UAV formation during the assembly phase and forms an optimal detection array. The UAV formation then tracks the target using the virtual geometric center based on the established rigid geometric configuration. The simulation experiments validate that the proposed model and method can enhance the passive detection effectiveness of the UAV formation, thereby achieving stable and efficient distributed cooperative tracking for the maneuvering target.
