Workshop on Human locomotion understanding for the design and control of next generation of humanoids and assistive devices
Gait is a fundamental skill of the bipedal form, and is a key area of investigation in both biomechanics and humanoid robotics. While humanoid robots have achieved impressive gains in their walking ability, they are still unable to reproduce the agility, flexibility, robustness and energy efficiency of human gait. Understanding and modeling human gait can improve our understanding of gait mechanics and control, and enable us to utilize these insights to improve the design and control of next generation humanoids and assistive devices.
In this workshop we aim to bring together leading researchers from both academia and industry in the area of human gait understanding, modeling and control, as well as researchers applying insights from gait studies to the design of robotic mechanisms and control strategies. In addition to lectures, the schedule will provide ample time for discussion and interaction. We also plan to organize an interactive/poster session to give younger researchers the opportunity to present and receive feedback on early stage work, as well as providing an opportunity for networking and additional discussion.
This workshop is sponsored by the RAS TC on Human Movement Understanding.
- Emel Demircan, California State University – Long Beach
- Dana Kulic, University of Waterloo
Morning Session: 10am - 1pm
10:00 - 10:10 Dana Kuli?, Welcome Remarks
10:10 – 11:00 Sung-Hee Lee, Motion Computing Laboratory, KAIST
- Momentum-based balance control for humanoid robots
Recent research suggests the importance of controlling rotational dynamics of a humanoid robot in balance maintenance and gait. In this talk, I will describe balance strategies that control both linear and angular momentum of the robot. The controller’s objective is defined in terms of the desired momenta or the desired center of pressure locations, and then the desired whole body motion is computed to realize the objectives, followed by computing the joint torques from the inverse dynamics. The balance strategy is demonstrated on a simulated humanoid robot under experiments such as recovery from unknown external pushes, balancing on non-level and moving supports, and stepping under larger pushes.
11:00 - 11:30 Coffee Break
11:30 - 12:15 Dana Kulic, Adaptive Systems Laboratory, University of Waterloo
- Gait Observation and Modelling for Clinical Gait Assessment
In this talk, we will describe a system for on-line measurement and analysis of human movement that can be used to provide feedback to patients and clinicians during the performance of rehabilitation exercises including functional gait. The system consists of wearable inertial measurement unit (IMU) sensors attached to the patient’s limbs. The IMU data is processed to estimate joint positions. We will describe an approach to improve the accuracy of pose estimation via on-line learning of the dynamic model of the movement, customized to each patient. We will present results of user studies analyzing the system capabilities for gait measurement of stroke patients undergoing gait rehabilitation, and demonstrating the significant benefits of feedback with patients undergoing rehabilitation following hip and knee replacement surgery.
12:15 - 13:00 Katja Mombaur, Optimization in Robotics and Biomechanics, University of Heidelberg
- Model-based optimization for analysis, design and control of physical assistive devices and humanoid robots
Gaining fundamental understanding of human movement is important not only for robotics, but also for many clinical or rehabilitation applications. Experimental recordings by motion capture systems, force plates, or EMG can give some insights, however for a precise dynamic reconstruction, dynamic models as well as advanced simulation and optimization techniques are required. We use model-based optimization for human movement analysis by fitting subject-specific dynamic models to recorded data, as well for motion generation or prediction by applying different optimality criteria to the human models. In this talk, I will present some of our work on dynamic modeling and optimization of human movement with and without physical assistive devices. The talk will cover the following topics:
- Optimization-based design of lower limb exoskeletons
- Analysis or running motions with prostheses
- Optimization-based analysis of unsupported human walking motions in different terrains
- Inverse optimal control of movements of cerebral palsy patients
- Optimization of motions of humanoid robots.
13:00 - 14:00 Lunch
Afternoon Session, 14:00 - 17:00
14:00 - 14:45 Federico Moro, Intelligent Robots and Autonomous Systems, CNR
- A Biologically-Inspired Whole-Body Control Approach
The work described in this presentation aims to advance the fast evolving state-of-the-art in Whole-Body Control, and to achieve this goal two main research directions were investigated. Firstly, a thorough analysis of human motion was performed, in order to better understand how humans can successfully handle composite tasks. Based on the experience gained through this analysis, the lesson learned was applied to synthesize a novel attractor-based Whole-Body Motion Control (WBMC) System, that presents a further step towards having robots being capable of operating in the real world.
The analysis of human motion led to the identification of the so-called kinematic Motion Primitives (kMPs) for both periodic and discrete movements. The kMPs are defined as invariant waveforms underlying human motion, and can combine to produce more complex movements that simultaneously achieve both discrete and periodic tasks.
Based on the experience gained with the kMPs an attractor-based Whole-Body Motion Control (WBMC) system was developed. A set of attractors was used to implement both balance (achieved by controlling the joint momentum and the gravitational stiffness of the robot) and movement features such as to avoid joint limits or to create end-effector movements. Superposing several of these attractors allows the generation of complex whole-body movements in order to perform different tasks simultaneously.
14:45 - 15:00 Mehdi Benellegue, LAAS-CNRS
- The Yoyo-Man
The Yoyo-Man project is a research action tending to explore the synergies of anthropomorphic locomotion. The seminal hypothesis is to consider the wheel as a plausible model of bipedal walking both in geometric and cognitive terms. In this presentation we report on preliminary results developed along three perspectives combining biomechanics, neurophysiology and robotics. From a motion capture data basis of human walkers we first identify the center of mass (CoM) as a geometric center from which the motions of the feet are organized. Then we show how rimless wheels that underly most passive walkers are better controlled when equipped with a stabilized mass on top of them and this, in a dynamical point of view. legs, CoM and head play complementary roles that define what we call the Yoyo-Man.
15:00 - 15:30 Coffee Break
15:30 - 16:30 Panel Discussion