Mohamed Elobaid

Mohamed Elobaid, Giulio Romualdi, Gabriele Nava et al.

In this paper we consider the problem of allowing a humanoid robot that is subject to a persistent disturbance, in the form of a payload-carrying task, to follow given planned footsteps. To solve this problem, we combine an online nonlinear centroidal Model Predictive Controller - MPC with a contact stable force parametrization. The cost function of the MPC is augmented with terms handling the disturbance and regularizing the parameter. The performance of the resulting controller is validated both in simulations and on the humanoid robot iCub. Finally, the effect of using the parametrization on the computational time of the controller is briefly studied.

Carlotta Sartore, Mohamed Elobaid, Lorenzo Rapetti et al.

Collaboration is central to human behavior, enabling tasks beyond individual capability. This ability arises from coordinating actions through internal representations of others, a concept known as shared intelligence. Additionally, humans are characterized by physical bodies and cognitive abilities that are optimized in response to their environment, a phenomenon referred to as embodied cognition. Designing humanoid robots that collaborate safely and effectively with people requires unifying these principles. Here we propose an architecture that integrates shared intelligence and embodied cognition to enable robots to physically collaborate with humans, where robot hardware and control are optimized for human metrics, using representations of the human body and motion intelligence. The ultimate goal is to achieve a form of shared embodied intelligence. Specifically, our architecture optimizes robot hardware and physical intelligence parameters with respect to human ergonomic metrics. This is accomplished by modeling human-robot interaction as a function of hardware configurations and embedding human models into the robot's physical intelligence. As a concrete implementation, we present the humanoid robot ergoCub, whose morphology and control have been optimized for collaborative tasks with humans. Our approach provides a framework for designing humanoid robots that prioritize human ergonomics at both the hardware and physical intelligence levels, with applications in industrial and assistive robotics.

Mohamed Elobaid, Stefano Dafarra, Ehsan Ranjbari et al.

This paper discusses the necessary considerations and adjustments that allow a recently proposed avatar system architecture to be used with different robotic avatar morphologies (both wheeled and legged robots with various types of hands and kinematic structures) for the purpose of enabling remote (intercontinental) telepresence under communication bandwidth restrictions. The case studies reported involve robots using both position and torque control modes, independently of their software middleware.

Mohamed Elobaid, Giulio Turrisi, Lorenzo Rapetti et al.

Nonlinear model predictive locomotion controllers based on the reduced centroidal dynamics are nowadays ubiquitous in legged robots. These schemes, even if they assume an inherent simplification of the robot's dynamics, were shown to endow robots with a step-adjustment capability in reaction to small pushes, and, moreover, in the case of uncertain parameters - as unknown payloads - they were shown to be able to provide some practical, albeit limited, robustness. In this work, we provide rigorous certificates of their closed loop stability via a reformulation of the centroidal MPC controller. This is achieved thanks to a systematic procedure inspired by the machinery of adaptive control, together with ideas coming from Control Lyapunov functions. Our reformulation, in addition, provides robustness for a class of unmeasured constant disturbances. To demonstrate the generality of our approach, we validated our formulation on a new generation of humanoid robots - the 56.7 kg ergoCub, as well as on a commercially available 21 kg quadruped robot, Aliengo.

Mohamed Elobaid, Yue Hu, Giulio Romualdi et al.

This paper proposes an architecture for achieving telexistence and teleoperation of humanoid robots. The architecture combines several technological set-ups, methodologies, locomotion and manipulation algorithms in a novel manner, thus building upon and extending works available in literature. The approach allows a human operator to command and telexist with the robot. Therefore, in this work we treat aspects pertaining not only to the proposed architecture structure and implementation, but also the human operator experience in terms of ability to adapt to the robot and to the architecture. Also the proprioception aspects and embodiment of the robot are studied through specific experimental results, which are also treated in a somewhat formal, albeit high-level manner. Application of the proposed architecture and experiments incorporating user training and experience are addressed using an illustrative bipedal humanoid robot, namely the iCub robot.