Gecko-like robot(Geckobot),an important branch of bionic robotics,is a robot that simulates gecko's capacity to climb walls and ceilings.The work environment of the traditional wall-climbing robot is greatly limited as the moving structure and adsorption principle of the robot have nothing to do with the real gecko.However,the adsorption principle and moving mode of the real gecko can provide a new way to break through the restrictions of the traditional wall-climbing robot.Inspired by the moving mechanism of geckos, this paper develops the Geckobot with motile body.Two types of Geckobots are addressed:one with compliant flat bar as the body,and the other with prismatic joint as the body.The compliant body not only resembles the moving mode of the real gecko body,but also simplifies the Geckobot's structure.The prismatic joint body is used to adapt the change of body length in ground-to-wall transition. The gait planning on the plane and the transition between perpendicular intersectional planes is discussed,with an emphasis on the analysis of the kinematics degree of freedom(DOF) and body posture.Central pattern generator(CPG) neural network is realized in LabVIEW and utilized to control Geckobot's movement.The CPG scheme in Lab VIEW is given,and how CPG is used to control Geckobot to turn or move forward is explored.Simulations are conducted in ADAMS to verify the feasibility of the structure design and gait planning and to acquire some parameters for practical Geckobot development.The experiment with Geckobot-Ⅰand Geckobot-Ⅱon their crawling capacity on the plane and the ground-to-wall transition finds that the robot can complete the crawling movement and ground-to-wall transition,verifying the feasibility of the structure design,gait planning and the CPG motion control.The Geckobot structure design approach,gait planning and the CPG motion control presented would be useful for the research on wall-climbing robots.
目的评价新设计的骨科机器人系统模块的精度及临床可行性。方法针对9例塑料胫骨模型,测量拼接图像上的胫骨全长,并同模型的实际长度进行比较,记录差值,统计分析拼接精度。针对1例尸体双下肢胫骨标本,人为制造胫骨骨折(伴有短缩成角畸形),拼接出骨折后的整条胫骨图像,在拼接图像上进行全程规划,确定骨折牵引距离,利用胫骨牵引支架进行自动化的定量闭合牵引,分析该模块的精度和有效性。同时,利用视频相机跟踪牵引动作中胫骨的长度变化,确保牵引过程的安全。针对1例胫骨骨折临床病例,进行拼接、规划和牵引,验证本模块的临床可行性。结果拼接一幅完整的胫骨图像需要术中采集7～10幅 C 臂图像,图像拼接精度为1.5 mm。图像采集的平均操作时间为1.5 min,拼接与规划的时间约为3 min,牵引支架安装和牵引操作的平均时间为4 min。尸体标本和临床试验在牵引后均达到骨折端复位准确,符合手术要求。结论科机器人系统全程规划模块能够为长骨骨折治疗提供有效、精确的牵引复位信息。该模块操作简单,并能达到微创手术的目的,同时还大大减少了手术中医生的 X 线放射损害。
