Torque-controlled stepping-strategy push recovery: Design and implementation on the iCub humanoid robot

  title={Torque-controlled stepping-strategy push recovery: Design and implementation on the iCub humanoid robot},
  author={Stefano Dafarra and Francesco Romano and Francesco Nori},
  journal={2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids)},
One of the challenges for the robotics community is to deploy robots which can reliably operate in real world scenarios together with humans. A crucial requirement for legged robots is the capability to properly balance on their feet, rejecting external disturbances. iCub is a state-of-the-art humanoid robot which has only recently started to balance on its feet. While the current balancing controller has proved successful in various scenarios, it still misses the capability to properly react… 

Figures from this paper

Synthesis of a Predictive Push-Recovery Controller: Simulation Results on the iCub Humanoid Robot
A Model Predictive Controller is conceived which enables the prediction of future evolutions of the robot, taking into account constraints switching when performing a step, and is validated through simulations, revealing higher robustness and reliability when executing the recovery strategy.
Optimal control based push recovery strategy for the iCub humanoid robot with series elastic actuators
  • Yue Hu, K. Mombaur
  • Computer Science, Engineering
    2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
  • 2017
This paper uses whole-body models combined with optimal control to explore the problem of push recovery in humanoid robots, and optimized for a stable motion that allows to perform recovery within one step.
A Predictive Momentum-Based Whole-Body Torque Controller: Theory and Simulations for the iCub Stepping
A Model Predictive Controller is conceived which determines a desired set of contact wrenches by predicting the future evolution of the robot, while taking into account constraints switching in case of steps, revealing high robustness and reliability when executing a recovery strategy.
A Receding Horizon Push Recovery Strategy for Balancing the iCub Humanoid Robot
This work implements a Receding Horizon control, also known as Model Predictive Control, to add the possibility to predict the future evolution of the robot, especially the constraints switching given by the hybrid nature of the system.
Predictive Whole-Body Control of Humanoid Robot Locomotion
This thesis tackles several aspects of the humanoid robot locomotion problem in a crescendo of complexity, and considers the single step push recovery problem, and generates and stabilize walking motions.
On the Emergence of Whole-Body Strategies From Humanoid Robot Push-Recovery Learning
This work applies model-free Deep Reinforcement Learning for training a general and robust humanoid push-recovery policy in a simulation environment and validate the method with extensive quantitative analyses in simulation, including out-of-sample tasks which demonstrate policy robustness and generalization, both key requirements towards real-world robot deployment.
A Dynamical System Approach for Adaptive Grasping, Navigation and Co-Manipulation with Humanoid Robots
An integrated approach that provides compliant control of an iCub humanoid robot and adaptive reaching, grasping, navigating and co-manipulating capabilities and achieves unprecedented adaptive behaviors for whole body manipulation is presented.
Push Recovery of a Quadrupedal Robot in the Flight Phase of a Long Jump
Legged robots are well-suited for operation in challenging natural environments, such as steep obstacles or vast gaps in the ground. Aside from difficult terrain, robots may also encounter
Humanoid Robot Pitch Axis Stabilization using Linear Quadratic Regulator with Fuzzy Logic and Capture Point
The proposed control system can maintain the humanoid robot’s stability around the pitch axis when subject to pendulum disturbances or even restraining force from a spring balance.
An Alternative Open Architecture Controller Design for the Bioloid Humanoid Robot
1 Abstract—Robot-based assistive technologies have in recent times, become an important research topic. Most commercial robots come with control systems which may support several types of user


iCub Whole-Body Control through Force Regulation on Rigid Non-Coplanar Contacts
The soundness of the entire control architecture is validated in a real scenario involving the robot iCub balancing and making contacts at both arms, and how to implement a joint torque control in the case of DC brushless motors is shown.
Stability analysis and design of momentum-based controllers for humanoid robots
It is numerically show that the application of state-of-the-art momentum-based control strategies may lead to unstable zero dynamics and propose simple modifications to the control architecture that avoid instabilities at the zero-dynamics level.
Whole-body motion integrating the capture point in the operational space inverse dynamics control
To achieve tasks that challenge the robot balance, the integration of the capture point (CP) in the operational-space inverse dynamics control framework is proposed letting the robot be able to simultaneously move its whole body satisfying other tasks.
Design of a Momentum-Based Control Framework and Application to the Humanoid Robot Atlas
A momentum-based control framework for floating-base robots and its application to the humanoid robot “Atlas” is presented and results for walking across rough terrain, basic manipulation, and multi-contact balancing on sloped surfaces are presented.
An experimental evaluation of a novel minimum-jerk cartesian controller for humanoid robots
The design of a Cartesian Controller for a generic robot manipulator that deals with a large number of degrees of freedom, produce smooth, human-like motion and is able to compute the trajectory on-line is described.
Capturability-based analysis and control of legged locomotion, Part 2: Application to M2V2, a lower-body humanoid
An algorithm that uses the ability of a legged system to come to a stop without falling by taking N or fewer steps and novel instantaneous capture point control strategies as approximations to control a humanoid robot is described.
Capture Point: A Step toward Humanoid Push Recovery
The well-known linear inverted pendulum model is extended to include a flywheel body and it is shown how to compute exact solutions of the capture region for this model, the region on the ground where a humanoid must step to in order to come to a complete stop.
Forces acting on a biped robot. Center of pressure-zero moment point
  • P. Sardain, G. Bessonnet
  • Engineering
    IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans
  • 2004
A virtual CoP-ZMP is defined, allowing us to extend the concept when walking on uneven terrain, and analyzing the evolution of the ground contact forces obtained from a human walker wearing robot feet as shoes.
Biped robot walking using gravity-compensated inverted pendulum mode and computed torque control
  • J. Park, Kyong D. Kim
  • Engineering
    Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146)
  • 1998
Simulation results show that the biped robot is more stable with the walking pattern generated by the proposed method combined with the controller than with the one by the inverted pendulum mode.
Push Recovery by stepping for humanoid robots with force controlled joints
Push Recovery Model Predictive Control (PR-MPC) is presented as a method for generating full-body step recovery motions after a large disturbance in humanoid robots.