Adaptive Whole-Body Dynamics: An Actuator Network System for Orchestrating Multijoint Movements

Adaptive Whole-Body Dynamics: An Actuator Network System for Orchestrating Multijoint Movements
复制标题

自适应全身动力学:用于协调多关节运动的执行器网络系统

DOI:
10.1109/mra.2016.2582725
复制
发表时间:
2016
期刊:
Robotics & Automation Magazine
影响因子:
--
通讯作者:
and Hiroshi Ishiguro
and Hiroshi Ishiguro
中科院分区:
--
文献类型:
--
作者:
Hideyuki ryu;Yoshihiro Nakata;Yutaka Nakamura;and Hiroshi Ishiguro

文献摘要

参考文献

被引文献

相似文献

自适应运动对于机器人在崎岖的地形和多变的地面上移动以完成各种任务至关重要[1]。数值计算的最新进展使机器人能够通过使用基于机器人身体和环境的精确模型的复杂控制框架在真实环境中操作。然而,获得精确的模型并不总是可行的,因为机器人的运动、位置、形状和刚度以及周围物体等因素会影响机器人的运动。特别是,与其他自主系统(如人类)的相互作用可能会导致机器人运动中的显著干扰。因此,机器人应该拥有强大的机制来对来自其周围的意外力量做出反应[2]、[3]。在自然界中可以看到这样的例子。动物能够有效地对这种干扰做出反应,是因为它们复杂的反应机制(例如,快速反应产生于肌肉骨骼系统的内在机械动力学)[4]。
Adaptive locomotion is crucial for robots that move across rough terrain and variable ground surfaces to complete various tasks [1]. Recent advances in numerical computation allow robots to operate in real environments by using complex control frameworks based on precise models of the robots' bodies and surroundings. However, it is not always feasible to obtain a precise model because factors such as the robot's movement, position, shape, and stiffness and surrounding objects affect the robot's motion. In particular, the interaction with other autonomous systems, such as humans, can result in significant disturbances in robot motion. Therefore, robots should possess robust mechanisms to react to unexpected forces from their surroundings [2], [3]. Examples are seen in nature. Animals can effectively react to such disturbances because of their elaborate reaction mechanisms (e.g., rapid reflexes arise from the intrinsic mechanical dynamics of the musculoskeletal system) [4].
物理连接的执行器网络:机器人肌肉骨骼系统的自组织机制
DOI: --
发表时间: 2014
期刊:
影响因子: --
作者:
Hideyuki Ryu;Yoshihiro Nakata;Yuya Okadome;Yutaka Nakamura;Hiroshi Ishiguro
通讯作者: Hiroshi Ishiguro
DOI: 10.1109/iros.2014.6942946
发表时间: 2014
期刊: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems
影响因子: --
作者:
J. P. Whitney;Matthew Glisson;Eric Brockmeyer;J. Hodgins
通讯作者: J. Hodgins
使用振荡器网络的四足机器人视觉引导运动控制
DOI: --
发表时间: 2007
期刊:
影响因子: --
作者:
T. Aragi;T. Kimura;K. Tsujita;T. Masuda
通讯作者: T. Masuda
采用数字液压系统的新型无级变速器
DOI: --
发表时间: 2015
期刊: IEEE/RJS International Conference on Intelligent RObots and Systems
影响因子: --
作者:
Zhenyu Gan;Katelyn E. Fry;R. Gillespie;C. Remy
通讯作者: C. Remy