Takashi Takuma

Biped robot design powered by antagonistic pneumatic actuators for multi-modal locomotion

An antagonistic muscle mechanism that regulates joint compliance contributes enormously to human dynamic locomotion. Antagonism is considered to be the key for realizing more than one locomotion mode. In this paper, we demonstrate how antagonistic pneumatic actuators can be utilized to achieve three dynamic locomotion modes (walking, jumping, and running) in a biped robot. Firstly, we discuss the contribution of joint compliance to dynamic locomotion, which highlights the importance of tunable compliance. Secondly, we introduce the design of a biped robot powered by antagonistic pneumatic actuators. Lastly, we apply simple feedforward controllers for realizing walking, jumping, and running and confirm the contribution of joint compliance to such multimodal dynamic locomotion. Based on the results, we can conclude that the antagonistic pneumatic actuators are superior candidates for constructing a human-like dynamic locomotor.

Pneumatic-driven jumping robot with anthropomorphic muscular skeleton structure

Human muscular skeleton structure plays an important role for adaptive locomotion. Understanding of its mechanism is expected to be used for realizing adaptive locomotion of a humanoid robot as well. In this paper, a jumping robot driven by pneumatic artificial muscles is designed to duplicate human leg structure and function. It has three joints and nine muscles, three of them are biarticular muscles. For controlling such a redundant robot, we take biomechanical findings into account: biarticular muscles mainly contribute to joint coordination whereas monoarticular muscles contribute to provide power. Through experiments, we find (1) the biarticular muscles realize coordinated movement of joints when knee and/or hip is extended, (2) the extension of the ankle does not lead to coordinated movement, and (3) we can superpose extension of the knee with that of the hip without losing the joint coordination. The obtained knowledge can be used not only for robots, but may also contribute to understanding of adaptive human mechanism.

Controlling the Walking Period of a Pneumatic Muscle Walker

In this paper, we investigate the limit cycle of a biped walker driven by pairs of pneumatic artificial muscles. We show, experimentally, that the period of the limit cycle changes when different control parameters are applied and estimate the relationship between the period and the parameters through trials. A step-by-step feedback controller is proposed to stabilize walking based on the estimated relation. The stability of the feedback controller is demonstrated by showing that the biped can walk down a stair.

3D bipedal robot with tunable leg compliance mechanism for multi-modal locomotion

It is expected that variation of leg compliance, that is determined not only by joint compliance but by joint angle, contributes to provide multi-modal locomotion such as walking, jumping and running by single robot. This paper describes a design of bipedal robot and feed forward controller that realize multi-modal locomotion by tuning appropriate leg compliance on individual locomotion. In order to tune physical leg compliance, we adopt rotational joints driven by antagonistic McKibben pneumatic muscles. Experimental results show that proper leg compliance provided by joint compliance and leg posture achieves a walking from standing and a sequential jumping. These results suggest that tunable leg compliance is powerful mechanism for bipedal robot to provide human-like multi-modal locomotion.

Facilitating multi-modal locomotion in a quadruped robot utilizing passive oscillation of the spine structure

An important topic in robotics is the design of a robot body using passive mechanical properties, such as viscoelasticity, to obtain energy-efficient locomotion at low computational costs. To achieve this aim, this study examines adopting a spinal structure with variable viscoelasticity and multiple joints. In order to investigate the effect of this spinal structure, a physical model of the spinal structure and a quadruped robot incorporating this design were developed, and the relationship between the gait pattern of the legs of the robot and viscoelasticity as a source of passive oscillation of the spinal structure was observed. The experimental results indicate that there are several interactions between the gait pattern and the viscoelasticity that can achieve one of various types of successful locomotion. These results suggest that the proposed spinal structure is a suitable body design for facilitating multi-modal locomotion at low computational costs.

Fast and Stable Learning of Quasi-Passive Dynamic Walking by an Unstable Biped Robot based on Off-Policy Natural Actor-Critic

Recently, many researchers on humanoid robotics are interested in quasi-passive-dynamic walking (quasi-PDW) which is similar to human walking. It is desirable that control parameters in quasi-PDW are automatically adjusted because robots often suffer from changes in their physical parameters and the surrounding environment. Reinforcement learning (RL) can be a key technology to this adaptability, and it has been shown that RL realizes quasi-PDW in a simulation study. To apply the existing method to controlling real robots, however, requires further improvement to accelerate its learning, otherwise the robots will break down before acquiring appropriate controls. To accelerate the learning, this study employs off-policy natural actor-critic (off-NAC), and applies it to an acquisition problem of quasi-PDW. The most important feature of the off-NAC is that it reuses the samples that has already been obtained by previous controllers. This study also shows an adaptive method of the learning rate. Simulation as well as real experiments demonstrate that fast and stable learning of quasi-PDW of an unstable biped robot can be realized by our modified off-NAC

Bouncing monopod with bio-mimetic muscular-skeleton system

Structure of a humanpsilas muscular-skeleton system is supposed to play an essential role for realizing dynamic locomotion such as jumping and running. This paper investigates the effectiveness of the human-like morphology for dynamic bouncing. We designed a monopod that had a bio-mimetic muscular-skeleton system utilizing pneumatic artificial muscles. Through the experiments, we confirmed that the biarticular muscles strongly governed the coordinated movement of its body. Utilizing such synergy brought by the muscles, a simple controller could realize stable bouncing even though the pneumatic artificial muscles have complicated characteristics.

Walking stabilization of biped with pneumatic actuators against terrain changes

Humans are supposed to utilize its joint elasticity to realize smooth and adaptive walking. Although such human-like biped walking is strongly affected by the terrain dynamics, it was not taken into account in robotic bipedalism since it is very difficult to model the dynamics formally. In this paper, instead of modeling the dynamics formally, we propose to estimate the relationship between actuation (air valve opening duration) and sensing (touch sensor information) by real walking trials, and to stabilize walking cycle by utilizing it. Since the terrain dynamics is involved in the relation, we can avoid to model it formally. We conducted walking experiments on various types of terrain to demonstrate the effectiveness of the proposed method.

Design and Control of 2D Biped that can Walk and Run with Pneumatic Artificial Muscles

We humans utilize body compliance provided by antagonistic muscles to realize dynamic locomotion such as walking, jumping, and running. In this paper, we introduce design of a biped robot driven by antagonistic pairs of artificial pneumatic muscles so that it can change joint compliance according to the desired dynamic locomotion. We then propose simple controllers for realizing walking, jumping, and running. Experimental results demonstrate that the robot can dynamically walk, jump, and run by the proposed controllers

Terrain Negotiation of a Compliant Biped Robot Driven by Antagonistic Artificial Muscles

Humans can negotiate various classes of terrain and realize adaptive bipedal walking, which is difficult for existing biped robots driven by electric motors. In this paper, a biped robot driven by antagonistic artificial muscles is developed that can negotiate several classes of terrain. The antagonistic muscles along with a simple control scheme can realize joint compliance without a time-delay. Not only does the compliance adapt the robot to terrain changes, but it also enables the robot to sense the terrain since the walking behavior is a result of the interaction between the dynamics of the robot body and the terrain. Experimental results demonstrate that the walking cycle changes according to joint compliance and the class of terrain. Utilizing the relationship between the two, the robot can regulate its walking cycle by changing its joint compliance. The compliance by such antagonistic muscles is a promising solution for realizing adaptive bipedal walking.