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Employing a Novel Gait Pattern Generator on a Social Humanoid Robot

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Employing a Novel Gait Pattern Generator on a Social Humanoid Robot Scientia Iranica A (2019) 26(4), 2154{2166 Sharif University of Technology Scientia Iranica Transactions A: Civil Engineering http://scientiairanica.sharif.edu Invited Paper Employing a novel gait pattern generator on a social humanoid robot A. Meghdaria;, S. Behzadipourb, and M. Abedib a. Social & Cognitive Robotics Laboratory, Center of Excellence in Design, Robotics, and Automation (CEDRA), School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran. b. School of Mechanical Engineering, Sharif University of Technology, Tehran, Iran. Received 11 February 2019; accepted 11 March 2019 KEYWORDS Abstract. This paper presents a novel Gait Pattern Generator (GPG) developed for the \Alice" social humanoid robot, which up to now lacked an appropriate walking pattern. Social robots; Due to the limitations of this robot, the proposed gate pattern generator was formulated Bipedal robots; based on a nine-mass model to decrease the modeling errors and the inverse kinematics of Gait pattern the whole lower-body was solved in such a way that the robot remained statically stable generating; during the movements. The main challenge of this work was to solve the inverse kinematics Inverse kinematics; of a 7-link chain with 12 degrees of freedom. For this purpose, a new graphical-numerical Static stability technique has been provided using the de nition of the kinematic equations of the robot condition. joints' Cartesian coordinates. This method resulted in a signi cant increase in the solution rate of calculations. Finally, a novel algorithm was developed for step-by-step displacement of the robot towards a desired destination in a two-dimensional space. Performance of the proposed gate pattern generator was evaluated both with a model of the robot in a MATLAB Simulink environment and in real experiments with the Alice humanoid robot. © 2019 Sharif University of Technology. All rights reserved. 1. Introduction of GPG planning. Some important characteristics of the robot, which a ect the GPG, are size and weight In recent years, social humanoid robots have emerged of the robot, number of Degrees of Freedom (DoF), with the goal of improving interaction between humans sensors and actuators, data processing performance, and environment [1-3]. Despite the complexities of and goals expected for the robot. However, gait pattern manufacturing and controlling bipedal and humanoid generating generally includes modelling, kinematic and robots, research on this class of robots is ongoing dynamic analysis, stability condition, path planning, and growing [4-6]. Gait pattern generation is one and controller design [7]. The nal objective of a GPG of the challenges of working with bipedal robots. is to generate robot joint trajectories that result in High degrees of freedom, robot stability, and unique stable robot walking. characteristics of each robot are some of the diculties Stability is an important problem in GPG plan- ning since ground contact forces must be compressive during the robot movement. In general, there are two *. Corresponding author. types of stability conditions: static and dynamic [8- E-mail addresses: [email protected] (A. Meghdari); [email protected] (S. Behzadipour); 11]. In static stability, the Ground Projection of the [email protected] (M. Abedi) Center of Mass (GCoM) of the robot is kept within the stability area (the convex hull of all contact points doi: 10.24200/sci.2019.21358 between the feet and the ground). Indeed, static A. Meghdari et al./Scientia Iranica, Transactions A: Civil Engineering 26 (2019) 2154{2166 2155 criterion is the oldest stability condition that was rst required to achieve the desired accuracy. Therefore, it suggested for a walking robot with massless legs [12]. is necessary to nd a solution to reduce the iterations. However, it has been proven that it is necessary to For example, Limonet al. [23] provided a two-step consider the mass of the legs to determine the robot approach for a six-DoF leg with a non-negligible o set stability when the leg mass is great enough [13]. This at the hip. At First, an approximate IK solution was condition is easier to implement, but the walking pro- derived analytically regardless of the o set at the hip. duced is usually too slow and not human-like because Then, this result was used as the initial condition for a of excessive movement in the frontal plane. On the numerical re ning procedure. other hand, keeping the Zero-Moment-Point (ZMP) in In this research, a GPG is developed for the the stability area is one of the dynamic conditions. humanoid robot \Alice" with the given Iranian name Although ZMP is a normal stability criterion, it is \Mina" [24], as shown in Figure 1. This robot has been not comprehensive. Thus, other criteria, such as used in autism treatment as a therapy assistant and in Foot Rotation Indicator (FRI) and Centroidal Moment English as a Second Language (ESL) education [25-28]. Pivot (CMP), have been derived to improve the ZMP Although this robot has the capability of walking, no method [14]. Also, due to the complex dynamics of a walking pattern has been designed for it thus far. To humanoid robot, it is impossible to generate a stable resolve this limitation, we found a walking pattern for walking pattern in real time using these conditions. Alice and implemented it. These conditions are usually used on a simple model of Considering the unique characteristics of this the robot. For this purpose, a one-mass model (linear robot (especially the non-negligible o set at the hip, inverted pendulum mode [15]), a two-mass model sensors, and actuators as well as the mass of the legs) (gravity-compensated inverted pendulum mode [16]), discussed in Section 2, a static stability with high and a three-mass model have been suggested [17,18]. accuracy has been used in the proposed GPG. To this Although some analytic gait planning is achieved using end, the GPG has been designed based on a nine- these simple models, it is necessary to compensate for mass model. Using this highly accurate model makes the modelling error. To this end, force sensors applied it necessary to solve the IK of the whole lower-body. to the soles of the robot are necessary to calculate the Hence, the main objective of this work was to solve real ZMP position. However, if a more precise model the IK of a 12-DoF chain. This was not common in (i.e., the multiple masses inverted pendulum mode [19]) the previously proposed GPG, because there was no is used, the ZMP equation becomes highly nonlinear analytical method for this problem. Previous iterative and complex. In this case, the robot joint trajectories methods for this case would be very time consuming, are calculated by a time-consuming iterative procedure, because forward kinematics (common in the numerical which makes it inappropriate for generating a real-time process of joint angles calculation) are very complicated walking pattern. for this 12-DoF chain. Also, it is not possible to Solving the Inverse Kinematics (IK) of humanoid nd an approximate analytical solution as the initial robots is also challenging because of their high number condition for this chain by ignoring the o set at the hip of DoF. Most commercial bipedal robots have 12 DoF (similar to the approach in [23]). Accordingly, a new in their lower-body (6 DoF in each leg) [20,21]. There graphical-numerical method is provided in this paper is no analytic IK solution for a whole lower-body with to reduce the calculation time. A set of kinematic such a structure. However, by using the simpler models equations based on the robot geometry are derived for (one-, two-, or three-mass model), it is possible to this purpose. Finally, the GPG is completed with an solve the IK of each leg (2 six-DoF chains) separately. algorithm for a step by step displacement of the robot Using these simpli cations, the trajectory of the body towards a desired destination in a two-dimensional of the robot can be calculated analytically. While it is space [29]. possible to provide a closed-form IK solution for each leg for most commercial biped robots (with 6 DoF in each leg) [22], this solution exists only if the 3 axes of the hip intersect each other at one point (that is, the hip is assumed as a spherical joint). One should note that it is possible to generate a gait pattern analytically fast enough for use in real- time applications only if there is no o set at the hip of the robot and the mass of the legs is light enough to use in simple models. Otherwise, iterative methods are probably the only solutions. However, these methods are not generally e ective because of Figure 1. Alice \Mina" robot and its components the expensive computation and large amount of time (dimensions are in centimetres) [24]. 2156 A. Meghdari et al./Scientia Iranica, Transactions A: Civil Engineering 26 (2019) 2154{2166 2. The Alice \Mina" humanoid robot Alice (renamed Mina for Persian dialogues) is an R50 model poorly designed and constructed by the Robokind Company [24,30]. It has a height of 69 cm; the masses of its components are presented in Figure 1. Also, it has 32 DoF. This robot, similar to most of the commercial bipedal robots, has 6 DoF in each leg (3 in the hip, one in the knee, and 2 in the ankle). Therefore, it is capable of walking on straight and curved paths, up and down stairs, and on sloped ground. These joints are actuated by Dynamixel RX-64. These servos are controlled by the internal computer of the robot. Java script is utilized to send the goal position of each joint to the internal computer.
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