Walking in the resonance with the COMAN robot with trajectories based on human kinematic motion primitives (kMPs)

被引:19
|
作者
Moro, Federico L. [1 ]
Tsagarakis, Nikos G. [1 ]
Caldwell, Darwin G. [1 ]
机构
[1] IIT, Dept Adv Robot, I-16163 Genoa, Italy
关键词
GENERATION; LOCOMOTION;
D O I
10.1007/s10514-013-9357-9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Research in humanoid robotics aims to develop autonomous systems that are able to assist humans in the performance of everyday tasks. Part of the robotics community claims that the best solution to guarantee the maximum adaptability of robots to the majority of human tasks is mimicry. Based on this premise both the structure of the human body and human behavior have been the focus of studies, with the aim of imitating and reproducing on robotic systems the results of millennia of human evolution. The research presented in this paper aims (i) at transferring the features of human locomotion to the COmpliant huMANoid (COMAN) robot, by means of kinematic motion primitives (kMPs) extracted from human subjects, and (ii) at improving the energetic performance of the walk of COMAN by exploiting its intrinsic compliance: it will be shown that, when the robot is walking at a gait frequency that is close to one of the main resonance frequencies of the mechanism, the springs contribute to tracking the human-like kMPs-based trajectories imposed, providing at the right time about 15 % of the energy required for locomotion, and that was previously stored.
引用
收藏
页码:331 / 347
页数:17
相关论文
共 50 条
  • [21] Motion Primitives for Designing Flexible Gesture Set in Human-Robot Interface
    Shon, Suwon
    Beh, Jounghoon
    Yang, Cheoljong
    Han, David K.
    Ko, Hanseok
    2011 11TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS), 2011, : 1501 - 1504
  • [22] A Falling Motion Strategy for Humanoids Based on Motion Primitives of Human Falling
    Meng, Libo
    Yu, Zhangguo
    Zhang, Weimin
    Chen, Xuechao
    Ceccarelli, Marco
    Huang, Qiang
    ADVANCES IN SERVICE AND INDUSTRIAL ROBOTICS, 2018, 49 : 264 - 272
  • [23] Learning Mobile Robot Motion Control from Demonstrated Primitives and Human Feedback
    Argall, Brenna
    Browning, Brett
    Veloso, Manuela
    ROBOTICS RESEARCH, 2011, 70 : 417 - +
  • [24] Motion Primitives for Human-Inspired Bipedal Robotic Locomotion: Walking and Stair Climbing
    Powell, Matthew J.
    Zhao, Huihua
    Ames, Aaron D.
    2012 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2012, : 543 - 549
  • [25] Concurrent Probabilistic Motion Primitives for Obstacle Avoidance and Human-Robot Collaboration
    Fu, Jian
    Wang, ChaoQi
    Du, JinYu
    Luo, Fan
    INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2019, PART VI, 2019, 11745 : 701 - 714
  • [26] Motion control for a walking companion robot with a novel human-robot interface
    Lv, Yunqi
    Gao, Xueshan
    Dai, Fuquan
    Liu, Yubai
    Shahzad, Adil
    Zhao, Jun
    Zhang, Tong
    INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS, 2016, 13 : 1 - 15
  • [27] KIT BASED MOTION GENERATOR FOR A SOFT WALKING ROBOT
    Schiller, Lars
    Maruthavanan, Duraikannan
    Seibel, Arthur
    Schlattmann, Josef
    PROCEEDINGS OF THE ASME 2020 INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION, IMECE2020, VOL 7A, 2020,
  • [28] Motion control of walking assistant robot based on comfort
    Tang, Aolin
    Cao, Qixin
    INDUSTRIAL ROBOT-THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH AND APPLICATION, 2012, 39 (06): : 564 - 579
  • [29] An Embedded Human Motion Capture System for An Assistive Walking Robot
    Zong, Cong
    Clady, Xavier
    Chetouani, Mohamed
    2011 IEEE INTERNATIONAL CONFERENCE ON REHABILITATION ROBOTICS (ICORR), 2011,
  • [30] Target human detection based on matching of walking motion signals between smartphone and robot for human following
    Otake, Naomichi
    Morioka, Kazuyuki
    2020 IEEE/SICE INTERNATIONAL SYMPOSIUM ON SYSTEM INTEGRATION (SII), 2020, : 410 - 415