相关论文: Long-time Self-body Image Acquisition and its Appl…
Tendon-driven musculoskeletal humanoids have many benefits in terms of the flexible spine, multiple degrees of freedom, and variable stiffness. At the same time, because of its body complexity, there are problems in controllability. First,…
The musculoskeletal humanoid has many benefits that human beings have, but the modeling of its complex flexible body is difficult. Although we have developed an online acquisition method of the nonlinear relationship between joints and…
Musculoskeletal humanoids are robots that closely mimic the human musculoskeletal system, offering various advantages such as variable stiffness control, redundancy, and flexibility. However, their body structure is complex, and muscle…
While the musculoskeletal humanoid has various biomimetic benefits, the modeling of its complex structure is difficult, and many learning-based systems have been developed so far. There are various methods, such as control methods using…
We proposed a method for learning the actual body image of a musculoskeletal humanoid for posture generation and object manipulation using inverse kinematics with redundancy in the shoulder complex. The effectiveness of this method was…
The musculoskeletal humanoid is difficult to modelize due to the flexibility and redundancy of its body, whose state can change over time, and so balance control of its legs is challenging. There are some cases where ordinary PID controls…
Passive elastic elements can contribute to stability, energetic efficiency, and impact absorption in both biological and robotic systems. They also add dynamical complexity which makes them more challenging to model and control. The impact…
Human body motions can be captured as a high-dimensional continuous signal using motion sensor technologies. The resulting data can be surprisingly rich in information, even when captured from persons with limited mobility. In this work, we…
While musculoskeletal humanoids have the advantages of various biomimetic structures, it is difficult to accurately control the body, which is challenging to model. Although various learning-based control methods have been developed so far,…
While the musculoskeletal humanoid has various biomimetic benefits, its complex modeling is difficult, and many learning control methods have been developed. However, for the actual robot, the hysteresis of its joint angle tracking is still…
Although robots with flexible bodies are superior in terms of the contact and adaptability, it is difficult to control them precisely. On the other hand, human beings make use of the surrounding environments to stabilize their bodies and…
Modeling and control of the human musculoskeletal system is important for understanding human motor functions, developing embodied intelligence, and optimizing human-robot interaction systems. However, current human musculoskeletal models…
Musculoskeletal humanoids have various biomimetic advantages, of which redundant muscle arrangement is one of the most important features. This feature enables variable stiffness control and allows the robot to keep moving its joints even…
The body structures of tendon-driven musculoskeletal humanoids are complex, and accurate modeling is difficult, because they are made by imitating the body structures of human beings. For this reason, we have not been able to move them…
Imitation learning has been actively studied in recent years. In particular, skill acquisition by a robot with a fixed body, whose root link position and posture and camera angle of view do not change, has been realized in many cases. On…
One of the important advantages of musculoskeletal humanoids is that the muscle arrangement can be easily changed and the number of muscles can be increased according to the situation. In this study, we describe an overall system of muscle…
Humans have impressive generalization capabilities when it comes to manipulating objects and tools in completely novel environments. These capabilities are, at least partially, a result of humans having internal models of their bodies and…
Humans and animals excel in combining information from multiple sensory modalities, controlling their complex bodies, adapting to growth, failures, or using tools. These capabilities are also highly desirable in robots. They are displayed…
Internal computational models of physical bodies are fundamental to the ability of robots and animals alike to plan and control their actions. These "self-models" allow robots to consider outcomes of multiple possible future actions,…
Humanoid robots are machines built with an anthropomorphic shape. Despite decades of research into the subject, it is still challenging to tackle the robot locomotion problem from an algorithmic point of view. For example, these machines…