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1、本科毕业论文外文文献及译文文献、资料题目：Walking Control algorithm of Biped Humanoid Robot 文献、资料来源：期刊文献、资料发表（出版）日期： 1999.6.3院（部）：理学院专 业：光信息科学与技术班级：光信112姓名：王若宇学号：2011121135指导教师：赵俊卿翻译日期：2015514外文文献:Walking Control algorithm of Biped Humanoid RobotMany studies on biped walking robots have been performed since 1970 1-4. Du
2、ring that period, biped walking robots have transformed into biped humanoid robots through the technological development.Furthermore, the biped humanoid robot has become a one of representative research topics in the intelligent robot research society. Many researchers anticipate that the humanoid r
3、obot industry will be the industry leader of the 21st century and we eventually enter an era of one robot in every home. The strong focus on biped humanoid robots stems from a long-standing desire for human-like robots.Furthermore, a human-like appearance is desirable for coexistence in a human-robo
4、t society. However, while it is not hard to develop a human-like biped robot platform, the realization of stable biped robot walking poses a considerable challenge. This is because of a lack of understanding on how humans walk stably. Furthermore, biped walking is an unstable successive motion of a
5、single support phase.Early biped walking of robots involved static walking with a very low walking speed 5,6. The step time was over 10 seconds per step and the balance control strategy was performed through the use of COG (Center Of Gravity). Hereby the projected point of COG onto the ground always
6、 falls within the supporting polygon that is made by two feet. During the static walking, the robot can stop the walking motion any time without falling down. The disadvantage of static walking is that the motion is too slow and wide for shifting the COGResearchers thus began to focus on dynamic wal
7、king of biped robots 7-9. It is fast walking with a speed of less than 1 second per step. If the dynamic balance can be maintained, dynamic walking is smoother and more active even when using small body motions. However,讦 the inertial forces generated from the acceleration of the robot body are not
8、suitably controlled, a biped robot easily falls down. In addition, during dynamic walking, a biped robot may falls down from disturbances and cannot stop the walking motion suddenly. Hence, the notion of ZMP (Zero Moment Point) was introduced in order to control inertial forces 10, 11. In the stable
9、 single support phase, the ZMP is equal to the COP (Center of Pressure) on the sole. The advantage of the ZMP is that it is a point where the center of gravity is projected onto the ground in the static state and a point where the total inertial force composed of the gravitational force and inertial
10、 force of mass goes through the ground in the dynamic state. If the ZMP strictly exists within the supporting polygon made by the feet, the robot never falls down. Most research groups have used the ZMP as a walking stability criterion of dynamic biped walking. To this end, the robot is controlled s
11、uch that the ZMP is maintained within the supporting polygon.In general, the walking control strategies using the ZMP can be divided into two approaches. First, the robot can be modeled by considering many point masses, the locations of the point masses and the mass moments of inertia of the linkage
12、s. The walking pattern is then calculated by solving ZMP dynamics derived from the robot model with a desired ZMP trajectory. During walking, sensory feed back is used to control the robot. Second, the robot is modeled by a simple mathematical model such as an inverted pendulum system, and then the
13、walking pattern is designed based on the limited information of a simple model and experimental hand tuning. During walking, many kinds of online controllers are activated to compensate the walking motion through the use of various sensory feedback data including the ZMP. The first approach can deri
14、ve a precise walking pattern that satisfies the desired ZMP trajectory, but it is hard to generate the walking pattern in real-time due to the large calculation burden. Further, if the mathematical model is different from the real robot, the performance is diminished. On the contrary, the second app
15、roach can easily generate the walking pattern online. However, many kinds of online controllers are needed to compensate the walking pattern in real-time, because the prescribed walking pattern cannot satisfy the desired ZMP trajectory. In addition, this method depends strongly on the sensory feedba
16、ck, and hence the walking ability is limited to the sensor s performance and requires considerable experimental hand tuning. The authors have developed biped humanoid robots through the second approach 12, 13. Specifically, various online controllers are activated and switched in the successive walking cycle.At present, biped humanoid robot research groups have developed their own robot platforms and dynamic walking control algorithms. For examp
