<strong>Background:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> Intraoperative surgical planning tools (ISPTs) used in curren...<strong>Background:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> Intraoperative surgical planning tools (ISPTs) used in current-generation robotic arm-assisted total knee arthroplasty (RTKA) systems (such as Navio</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;"> and MAKO</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;">) involve employment of postoperative passive joint balancing. This results in improper ligament tension, which may negatively impact joint stability, which, in turn, may adversely affect patient function after TKA. </span><b><span style="font-family:Verdana;">Methods:</span></b><span style="font-family:Verdana;"> A simulation-enhanced ISPT (SEISPT) that provides insights relating to postoperative active joint mechanics was developed. This involved four steps: 1) validation of a multi-body musculoskeletal model;2) optimization of the validated model;3) use of the validated and optimized model to derive knee performance equations (KPEs), which are equations that relate implant component characteristics to implant component biomechanical responses;and 4) optimization of the KPEs with respect to these responses. In a proof-of-concept study, KPEs that involved two</span></span><span style="font-family:Verdana;"> </span><span style="font-family:Verdana;">com</span><span style="font-family:Verdana;">- </span><span style="font-family:;" "=""><span style="font-family:Verdana;">ponent biomechanical responses that have been shown to strongly correlate with poor proprioception (a common patient complaint post-TKA) were used to calculate optimal positions and orientations of the femoral and tibial components in the TKA design implanted in one subject (as reported in a publicly-available dataset). </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> The differences between the calculated implant positions and orientations and the corresponding achieved values for the implant components in the subject were not similar to component position and orientation errors reported in biomechanical literature studies involving Navio</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;"> and MAKO</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;">. Also, we indicate how SEISPT could be incorporated into the surgical workflow of Navio</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;"> with minimal disruption and increase in cost. </span><b><span style="font-family:Verdana;">Conclusion:</span></b><span style="font-family:Verdana;"> SEISPT is a plausible alternative to current-gen</span></span><span style="font-family:Verdana;">- </span><span style="font-family:Verdana;">eration ISPTs.</span>展开更多
One of the most important problems in robot kinematics and control is, finding the solution of Inverse Kinematics. Inverse kinematics computation has been one of the main problems in robotics research. As the Complexi...One of the most important problems in robot kinematics and control is, finding the solution of Inverse Kinematics. Inverse kinematics computation has been one of the main problems in robotics research. As the Complexity of robot increases, obtaining the inverse kinematics is difficult and computationally expensive. Traditional methods such as geometric, iterative and algebraic are inadequate if the joint structure of the manipulator is more complex. As alternative approaches, neural networks and optimal search methods have been widely used for inverse kinematics modeling and control in robotics This paper proposes neural network architecture that consists of 6 sub-neural networks to solve the inverse kinematics problem for robotics manipulators with 2 or higher degrees of freedom. The neural networks utilized are multi-layered perceptron (MLP) with a back-propagation training algorithm. This approach will reduce the complexity of the algorithm and calculation (matrix inversion) faced when using the Inverse Geometric Models implementation (IGM) in robotics. The obtained results are presented and analyzed in order to prove the efficiency of the proposed approach.展开更多
为克服传统白鲸优化算法(Beluga Whale Optimization,BWO)在3-5-3多项式插值机械臂轨迹优化中存在的路径长、时间耗费高及易陷入局部最优的问题,本文提出了一种增强型白鲸-蝠鲼融合优化算法(Enhanced Beluga Whale and manta ray fusion...为克服传统白鲸优化算法(Beluga Whale Optimization,BWO)在3-5-3多项式插值机械臂轨迹优化中存在的路径长、时间耗费高及易陷入局部最优的问题,本文提出了一种增强型白鲸-蝠鲼融合优化算法(Enhanced Beluga Whale and manta ray fusion Optimization algorithm,EBWO).该算法以机械臂最优运动时间为目标,构建约束优化模型,并通过增广拉格朗日乘子法转化为无约束形式.首先,利用改进的对数非线性Halton混沌序列优化种群初始化,提高搜索多样性与质量;其次,设计多方向正余弦白鲸位置更新机制,增强开发阶段搜索能力;再次,在中期迭代阶段引入改进的蝠鲼旋风链式觅食策略,并结合Levy飞行机制构建新觅食因子,以强化局部开发与全局跳跃能力;最后,提出基于资源竞争耦合机制的自适应鲸落策略,并引入量子隧穿效应,以提升算法跳出局部最优的能力与收敛速度.实验结果表明:在3-5-3轨迹优化中,EBWO较于传统BWO将时间优化效果提升了8.69%,并且与未优化的轨迹相比,优化后的时间缩短了42.13%.这一结果验证了其在复杂优化任务时的有效性与实用性.展开更多
文摘<strong>Background:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> Intraoperative surgical planning tools (ISPTs) used in current-generation robotic arm-assisted total knee arthroplasty (RTKA) systems (such as Navio</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;"> and MAKO</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;">) involve employment of postoperative passive joint balancing. This results in improper ligament tension, which may negatively impact joint stability, which, in turn, may adversely affect patient function after TKA. </span><b><span style="font-family:Verdana;">Methods:</span></b><span style="font-family:Verdana;"> A simulation-enhanced ISPT (SEISPT) that provides insights relating to postoperative active joint mechanics was developed. This involved four steps: 1) validation of a multi-body musculoskeletal model;2) optimization of the validated model;3) use of the validated and optimized model to derive knee performance equations (KPEs), which are equations that relate implant component characteristics to implant component biomechanical responses;and 4) optimization of the KPEs with respect to these responses. In a proof-of-concept study, KPEs that involved two</span></span><span style="font-family:Verdana;"> </span><span style="font-family:Verdana;">com</span><span style="font-family:Verdana;">- </span><span style="font-family:;" "=""><span style="font-family:Verdana;">ponent biomechanical responses that have been shown to strongly correlate with poor proprioception (a common patient complaint post-TKA) were used to calculate optimal positions and orientations of the femoral and tibial components in the TKA design implanted in one subject (as reported in a publicly-available dataset). </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> The differences between the calculated implant positions and orientations and the corresponding achieved values for the implant components in the subject were not similar to component position and orientation errors reported in biomechanical literature studies involving Navio</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;"> and MAKO</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;">. Also, we indicate how SEISPT could be incorporated into the surgical workflow of Navio</span><sup><span style="font-size:12px;font-family:Verdana;"><span lang="ZH-CN" style="font-size:12pt;font-family:宋体;">®</span></span></sup><span style="font-family:Verdana;"> with minimal disruption and increase in cost. </span><b><span style="font-family:Verdana;">Conclusion:</span></b><span style="font-family:Verdana;"> SEISPT is a plausible alternative to current-gen</span></span><span style="font-family:Verdana;">- </span><span style="font-family:Verdana;">eration ISPTs.</span>
文摘One of the most important problems in robot kinematics and control is, finding the solution of Inverse Kinematics. Inverse kinematics computation has been one of the main problems in robotics research. As the Complexity of robot increases, obtaining the inverse kinematics is difficult and computationally expensive. Traditional methods such as geometric, iterative and algebraic are inadequate if the joint structure of the manipulator is more complex. As alternative approaches, neural networks and optimal search methods have been widely used for inverse kinematics modeling and control in robotics This paper proposes neural network architecture that consists of 6 sub-neural networks to solve the inverse kinematics problem for robotics manipulators with 2 or higher degrees of freedom. The neural networks utilized are multi-layered perceptron (MLP) with a back-propagation training algorithm. This approach will reduce the complexity of the algorithm and calculation (matrix inversion) faced when using the Inverse Geometric Models implementation (IGM) in robotics. The obtained results are presented and analyzed in order to prove the efficiency of the proposed approach.
