Torque-Controlled Stepping-Strategy Push Recovery: Design and Implementation on the iCub Humanoid Robot

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 to strong pushes by taking steps. This paper goes in this direction. It proposes and implements a control strategy based on the Capture Point concept [1]. Instead of relying on position control, like most of Capture Point related approaches, the proposed strategy generates references for the momentum-based torque controller already implemented on the iCub, thus extending its capabilities to react to external disturbances, while retaining the advantages of torque control when interacting with the environment. Experiments in the Gazebo simulator and on the iCub humanoid robot validate the proposed strategy

Momentum Control of Humanoid Robots with Series Elastic Actuators

Humanoid robots may require a degree of compliance at the joint level for improving efficiency, shock tolerance, and safe interaction with humans. The presence of joint elasticity, however, complexifies the design of balancing and walking controllers. This paper proposes a control framework for extending momentum based controllers developed for stiff actuators to the case of series elastic actuators. The key point is to consider the motor velocities as an intermediate control input, and then apply high-gain control to stabilise the desired motor velocities achieving momentum control. Simulations carried out on a model of the robot iCub verify the soundness of the proposed approach

Automatic Gain Tuning of a Momentum Based Balancing Controller for Humanoid Robots

This paper proposes a technique for automatic gain tuning of a momentum based balancing controller for humanoid robots. The controller ensures the stabilization of the centroidal dynamics and the associated zero dynamics. Then, the closed-loop, constrained joint space dynamics is linearized and the controller's gains are chosen so as to obtain desired properties of the linearized system. Symmetry and positive definiteness constraints of gain matrices are enforced by proposing a tracker for symmetric positive definite matrices. Simulation results are carried out on the humanoid robot iCub.Comment: Accepted at IEEE-RAS International Conference on Humanoid Robots (HUMANOIDS). 201

Whole-body multi-contact motion in humans and humanoids: Advances of the CoDyCo European project

International audienceTraditional industrial applications involve robots with limited mobility. Consequently, interaction (e.g. manipulation) was treated separately from whole-body posture (e.g. balancing), assuming the robot firmly connected to the ground. Foreseen applications involve robots with augmented autonomy and physical mobility. Within this novel context, physical interaction influences stability and balance. To allow robots to surpass barriers between interaction and posture control, forthcoming robotic research needs to investigate the principles governing whole-body motion and coordination with contact dynamics. There is a need to investigate the principles of motion and coordination of physical interaction, including the aspects related to unpredictability. Recent developments in compliant actuation and touch sensing allow safe and robust physical interaction from unexpected contact including humans. The next advancement for cognitive robots, however, is the ability not only to cope with unpredictable contact, but also to exploit predictable contact in ways that will assist in goal achievement. Last but not least, theoretical results needs to be validated in real-world scenarios with humanoid robots engaged in whole-body goal-directed tasks. Robots should be capable of exploiting rigid supportive contacts, learning to compensate for compliant contacts, and utilising assistive physical interaction from humans. The work presented in this paper presents state-of-the-art in these domains as well as some recent advances made within the framework of the CoDyCo European project

force and motion capture system based on distributed micro accelerometers gyros force and tactile sensing

Motion capture is a powerful tool used in a large range of applications towards human movement analysis. Although it is a well-established technique, its main limitation is the lack of dynamic information such as forces and torques during the motion capture. In this paper, we present a novel approach for human wearable dynamic (WearDY) motion capture for the simultaneous estimation of whole-body forces along with the motion. Our conceptual framework encompasses traditional passive markers based methods, inertial and contact force sensor modalities and harnesses a probabilistic computa- tional framework for estimating dynamic quantities originally proposed in the domain of humanoid robot control. We present experimental analysis of our framework on subjects performing a two degrees-of-freedom bowing task and we estimate the motion and dynamic quantities. The results demonstrate the validity of the proposed method. We discuss the implications of our proposal towards the design of a novel wearable force and motion capture suit and its applications