生物の二関節間筋腱複合体を規範とした脚ロボットの開発

電気通信大学201

Muscle‐Like Compliance in Knee Articulations Improves Biped Robot Walkings

This chapter focuses on the compliance effect of dynamic humanoid robot walking. This compliance is generated with an articular muscle emulator system, which is designed using two neural networks (NNs). One NN models a muscle and a second learns to tune the proportional integral derivative (PID) of the articulation DC motor, allowing it to behave analogously to the muscle model. Muscle emulators are implemented in the knees of a three‐dimensional (3D) simulated biped robot. The simulation results show that the muscle emulator creates compliance in articulations and that the dynamic walk, even in walk‐halt‐stop transitions, improves. If an external thrust unbalances the biped during the walk, the muscle emulator improves the control and prevents the robot from falling. The total power consumption is significantly reduced, and the articular trajectories approach human trajectories

Gastrocnemius and Power Amplifier Soleus Spring-Tendons Achieve Fast Human-like Walking in a Bipedal Robot

Legged locomotion in humans is governed by natural dynamics of the human body and neural control. One mechanism that is assumed to contribute to the high efficiency of human walking is the impulsive ankle push-off, which potentially powers the swing leg catapult. However, the mechanics of the human lower leg with its complex muscle-tendon units spanning over single and multiple joints is not yet understood. Legged robots allow testing the interaction between complex leg mechanics, control, and environment in real-world walking gait. We developed a 0.49m tall, 2.2kg anthropomorphic bipedal robot with Soleus and Gastrocnemius muscle-tendon units represented by linear springs, acting as mono- and biarticular elastic structures around the robot's ankle and knee joints. We tested the influence of three Soleus and Gastrocnemius spring-tendon configurations on the ankle power curves, the coordination of the ankle and knee joint movements, the total cost of transport, and walking speed. We controlled the robot with a feed-forward central pattern generator, leading to walking speeds between 0.35m/s and 0.57m/s at 1.0Hz locomotion frequency, at 0.35m leg length. We found differences between all three configurations; the Soleus spring-tendon modulates the robot's speed and energy efficiency likely by ankle power amplification, while the Gastrocnemius spring-tendon changes the movement coordination between ankle and knee joints during push-off.Comment: Data and code repository at https://doi.org/10.17617/3.BQ2PZ9. Video on youtube at https://youtu.be/T79pKLQ47X

Simulating a Flexible Robotic System based on Musculoskeletal Modeling

Humanoid robotics offers a unique research tool for understanding the human brain and body. The synthesis of human motion is a complex procedure that involves accurate reconstruction of movement sequences, modeling of musculoskeletal kinematics, dynamics and actuation, and characterization of reliable performance criteria. Many of these processes have much in common with the problems found in robotics research, with the recent advent of complex humanoid systems. This work presents the design and development of a new-generation bipedal robot. Its modeling and simulation has been realized by using an open-source software to create and analyze dynamic simulation of movement: OpenSim. Starting from a study by Fuben He, our model aims to be used as an innovative approach to the study of a such type of robot in which there are series elastic actuators represented by active and passive spring components in series with motors. It has provided of monoarticular and biarticular joint in a very similar manner to human musculoskeletal model. This thesis is only the starting point of a wide range of other possible future works: from the control structure completion and whole-body control application, to imitation learning and reinforcement learning for human locomotion, from motion test on at ground to motion test on rough ground, and obviously the transition from simulation to practice with a real elastic bipedal robot biologically-inspired that can move like a human bein