Diamond turning based on a fast tool servo(FTS)is widely used in freeform optics fabrication due to its high accuracy and machining efficiency.As a new trend,recently developed high-frequency and long-stroke FTS units...Diamond turning based on a fast tool servo(FTS)is widely used in freeform optics fabrication due to its high accuracy and machining efficiency.As a new trend,recently developed high-frequency and long-stroke FTS units are independently driven by a separate control system from the machine tool controller.However,the tool path generation strategy for the independently controlled FTS is far from complete.This study aims to establish methods for optimizing tool path for the independent control FTS to reduce form errors in a single step of machining.Different from the conventional integrated FTS control system,where control points are distributed in a spiral pattern,in this study,the tool path for the independent FTS controller is generated by the ring method and the mesh method,respectively.The machined surface profile is predicted by simulation and the parameters for the control point generation are optimized by minimizing the deviation between the predicted and the designed surfaces.To demonstrate the feasibility of the proposed tool path generation strategies,cutting tests of a two-dimensional sinewave and a micro-lens array were conducted and the results were compared.As a result,after tool path optimization,the peak-to-valley form error of the machined surface was reduced from 429 nm to 56 nm for the two-dimensional sinewave by using the ring method,and from 191 nm to 103 nm for the micro-lens array by using the mesh method,respectively.展开更多
为提高果园机器人在果园中作业的自主性、安全性和效率,需要进行有效合理的运动规划。针对传统RRT^(*)(Rapidly exploring random tree star)全局路径规划算法在连续走廊式环境下存在搜索效率低、采样点利用率低、生成路径折线多转角大...为提高果园机器人在果园中作业的自主性、安全性和效率,需要进行有效合理的运动规划。针对传统RRT^(*)(Rapidly exploring random tree star)全局路径规划算法在连续走廊式环境下存在搜索效率低、采样点利用率低、生成路径折线多转角大等问题,以阿克曼底盘果园喷雾机器人为运动模型,提出一种改进双向RRT^(*)的果园喷雾机器人运动规划算法。首先,根据激光雷达建立果园二维平面地图,将果树和障碍物均视为障碍物区域,并结合喷雾机器人本体尺寸,对障碍物进行膨胀化处理;然后,通过改进双向RRT^(*)算法搜索路径,搜索路径过程中结合动态末梢节点导向和势场导向进行偏置采样,并对初步生成的路径进行路径点去冗余以及相邻折线段转角约束处理;最后,采用三阶准均匀B样条曲线对处理后的路径点进行轨迹优化,在优化过程中主要考虑轨迹的碰撞检测和喷雾机器人底盘曲率约束。试验结果表明,相较于传统双向RRT^(*)算法,本文所提出的改进算法规划时间平均减少57.5%,采样点利用率平均提高28.55个百分点,最终路径长度平均缩短7.14%;经三阶准均匀B样条曲线优化后所得轨迹在有、无障碍物两种环境下均满足喷雾机器人最大曲率约束,且仅在换行以及障碍物处存在转弯行为,符合喷雾机器人作业轨迹条件,提高了喷雾机器人的工作效率和自主性。展开更多
基金supported by Japan Society for the Promotion of Science,Grant-in-Aid for Scientific Research(B),Project Number 21H01230.
文摘Diamond turning based on a fast tool servo(FTS)is widely used in freeform optics fabrication due to its high accuracy and machining efficiency.As a new trend,recently developed high-frequency and long-stroke FTS units are independently driven by a separate control system from the machine tool controller.However,the tool path generation strategy for the independently controlled FTS is far from complete.This study aims to establish methods for optimizing tool path for the independent control FTS to reduce form errors in a single step of machining.Different from the conventional integrated FTS control system,where control points are distributed in a spiral pattern,in this study,the tool path for the independent FTS controller is generated by the ring method and the mesh method,respectively.The machined surface profile is predicted by simulation and the parameters for the control point generation are optimized by minimizing the deviation between the predicted and the designed surfaces.To demonstrate the feasibility of the proposed tool path generation strategies,cutting tests of a two-dimensional sinewave and a micro-lens array were conducted and the results were compared.As a result,after tool path optimization,the peak-to-valley form error of the machined surface was reduced from 429 nm to 56 nm for the two-dimensional sinewave by using the ring method,and from 191 nm to 103 nm for the micro-lens array by using the mesh method,respectively.
文摘为提高果园机器人在果园中作业的自主性、安全性和效率,需要进行有效合理的运动规划。针对传统RRT^(*)(Rapidly exploring random tree star)全局路径规划算法在连续走廊式环境下存在搜索效率低、采样点利用率低、生成路径折线多转角大等问题,以阿克曼底盘果园喷雾机器人为运动模型,提出一种改进双向RRT^(*)的果园喷雾机器人运动规划算法。首先,根据激光雷达建立果园二维平面地图,将果树和障碍物均视为障碍物区域,并结合喷雾机器人本体尺寸,对障碍物进行膨胀化处理;然后,通过改进双向RRT^(*)算法搜索路径,搜索路径过程中结合动态末梢节点导向和势场导向进行偏置采样,并对初步生成的路径进行路径点去冗余以及相邻折线段转角约束处理;最后,采用三阶准均匀B样条曲线对处理后的路径点进行轨迹优化,在优化过程中主要考虑轨迹的碰撞检测和喷雾机器人底盘曲率约束。试验结果表明,相较于传统双向RRT^(*)算法,本文所提出的改进算法规划时间平均减少57.5%,采样点利用率平均提高28.55个百分点,最终路径长度平均缩短7.14%;经三阶准均匀B样条曲线优化后所得轨迹在有、无障碍物两种环境下均满足喷雾机器人最大曲率约束,且仅在换行以及障碍物处存在转弯行为,符合喷雾机器人作业轨迹条件,提高了喷雾机器人的工作效率和自主性。
