Raibert et al. developed a running robot with a single linear leg [1]. The bipedal robot ATRIAS has a four-bar leg mechanism that includes a series of elastic springs [2,3]. Hyon et al. developed a biologically inspired robot based on a dog-leg model [4]. However, these robots do not have a human-like structure. Some studies have shown that bipedal humanoid robots can run [5,6,7,8,9]. For example, the Advanced Step in Innovative MObility (ASIMO) humanoid robot, which was designed and developed by Honda, can run at a speed of 2.5 m/s [10]. Toyota’s bipedal humanoid robot can run using a zero-moment-point (ZMP)-based running control system [11]. The athlete robot developed by Niiyama et al. has a human-like musculoskeletal system built to execute dynamic motions, such as running [12]. The bipedal robot MABEL, developed by researchers at the University of Michigan, has leg elasticity that originates from a leaf spring. It is the fastest-running of all currently available bipedal robots, having achieved a speed of 3 m/s with axial constraints on the y-axis [13].
However, present humanoid robots cannot run as fast and stably as human beings, who can run at speeds ranging between 2 m/s and 13 m/s. The reason that ordinary humanoid robots cannot run as fast and stably as humans because they require both a large power output for kicking the ground and various stabilization control methods. In general, to increase the power output, actuators having large power output capacity are required. However, high power actuators are heavy and their use in the humanoid robots renders the robots heavy. Moreover, the actuators require higher power. Therefore, it is difficult to design humanoid robots that can achieve high power output and are light enough to jump. Ordinary humanoid robots can attain a power output of approximately 3.5 W/kg for the joints in the leg; however, humans generate around 16.7 W/kg in leg joints while running [14]. In addition, various stabilization control methods such as considering the center of mass position, landing point, ground reaction force, and linear and angular momentum, are needed for stable running. However, present running stabilization methods do not consider motion during the flight phase.
A bipedal robot walks on a simple principle UVC (Upper body Vertical Control). A physics simulation ODE (Open Dynamics Engine) was used to validate a stability control of a robot when external force is applied to the robot. Generally, walking control of a robot requires complex dynamic movement calculation; however, this particular robot does not rely on a dynamic calculation at all. Instead, it uses the posture reflex (mechanical compliance) as seen in a human body using only about 100 steps of program (lines of code). In the video, you see the robot stepping backward to maintain balance when the external force is applied. This is not due to the pre-programmed code, but due to the UVC causing randomized reactive actions in order to maintain balance.
https://www.technologyx2.com/blog_dr_guero
Download the following 4 files and add them to your project using ODE’s Solution Explorer,
it will work.
biped.cpp download (Updated on June 1,2021)
This is the ODE main routine. Here, a 3D object is generated,
and the 3D robot is driven by the joint drive amount specified by the walking control unit below.
biped.h download
ODE main routine header file.
core.cpp download (Updated on June 1,2021)
This is the main body of the walking control unit. The three elements of walking,
① basic motion, ② postural reflex (UVC), and ③ timing control (CPG) are integrated
to generate walking motion.
core.h download (Updated on June 1,2021)
Header file of the walking control unit.
Explain the operation.
The following operations can be performed by key input.
w: Start walking
u: Specify UVC (upper body vertical control) enable / disable as an alternative.
When the body is blue, UVC is enabled,and when it is red, UVC is disabled.
r: Reset (return to the initial position)
q: Finished