Philippe Souères

Supernumerary robotic limbs (SLs) could extend human motor capabilities beyond the natural body, yet most demonstrations have been limited to simple, quasi-static tasks or direct teleoperation under visual control. Whether humans can safely and intuitively collaborate with autonomous SLs during complex, dynamic tasks remains unknown. We studied this question in a demanding assembly task requiring coordinated transport and handovers of a long object, which could not be completed by a single person. We developed a reconfigurable backpack platform mounting up to four high-payload robotic arms, together with safety-aware motion planning that generates human-compatible trajectories from task states without training data. Despite the SLs operating out of sight, participants adapted quickly, completed the task reliably, and reported low cognitive demand alongside high perceived safety and predictability. Kinematic and force analyses showed that control design governed both movement fluency and whole-body stability: faster limb motions yielded smoother interactions and shorter completion times, and a mirrored coordination strategy–in which one robotic limb counterbalanced the other–further shortened duration and reduced variability in left-right ground reaction force differences during co-manipulation. These results show that humans can integrate autonomous wearable limbs as out-of-sight partners in dynamic whole-body collaboration, and delineate behavioral and control principles underpinning fluency, stability, and usability in human augmentation.

This letter outlines a bi-level algorithm to concurrently optimize robot hardware and control parameters in order to minimize energy consumption during the execution of tasks and to ensure robust performance. The outer loop consists in a genetic algorithm that optimizes the co-design variables according to the system average performance when tracking a locally optimal trajectory in perturbed simulations. The tracking controller exploits the locally optimal feedback gains computed in the inner loop with a Differential Dynamic Programming algorithm, which finds the optimal reference trajectories. Our simulations feature a complete actuation model, including friction compensation and bandwidth limits. This strategy can potentially account for arbitrary perturbations, and discards solutions that cannot robustly meet the task requirements. The results show improved performance of the designed platform in realistic application scenarios, autonomously leading to the selection of lightweight and more transparent hardware.

This letter presents significant improvements to the nominal control architecture of the open-access Solo-12 quadruped that were done to implement and compare different centroidal Model Predictive Controllers (MPC). This work was motivated by our previous study in which various MPC schemes of increasing complexity were tested in simulation. They range from a simplified linearized model with contact points fixed by a heuristic, to a nonlinear one that also optimizes the contact points locations. We describe the developments that were necessary to implement such control schemes on the real robot while doubling its maximum velocity. Notably, to synthesize a stable whole-body controller, the inverse dynamics resolution was replaced by a mixed inverse kinematics and quadratic programming scheme. These developments enabled the successful deployments of the various centroidal MPCs on Solo-12. Experimental results show that all MPCs lead to quite similar performances with the proposed whole-body controller and, as a consequence, do not confirm the result of previous simulation study that concluded on the preeminence of the nonlinear centroidal MPC optimizing both the center of mass trajectory and the foot placements.

During cyclic actuation, conducting polymer based artificial muscles are often creeping from the initial movement range. One of the likely reasons of such behaviour is unbalanced charging during conducting polymer oxidation and reduction. To improve the actuation reversibility and subsequently the long time performance of ionic actuators, we suggest using spray-coated carbon nanotube (CNT) carpets on the surface of the conducting polymer electrodes. We show that carbon nanotubes facilitate a conducting polymer redox reaction and improve its reversibility. Consequently, in the long term, charge accumulation in the polymer film is avoided leading to a significantly improved lifetime performance during cycling actuation. To our knowledge, it is the first time a simple solution to an actuator creeping problem has been suggested.

Robots and Humans have to share the same environment more and more often. In the aim of steering robots in a safe and convenient manner among humans it is required to understand how humans interact with them. This work focuses on collision avoidance between a human and a robot during locomotion. Having in mind previous results on human obstacle avoidance, as well as the description of the main principles which guide collision avoidance strategies, we observe how humans adapt a goal-directed locomotion task when they have to interfere with a mobile robot. Our results show differences in the strategy set by humans to avoid a robot in comparison with avoiding another human. Humans prefer to give the way to the robot even when they are likely to pass first at the beginning of the interaction.

Despite a growing interest in conducting polymer based actuators, a robust fabrication technique is still needed. We suggest a fabrication method that allows fast production of conducting polymer actuators from commercially available polyvinylidene flouride membranes (PVDF) and a PEDOT/PSS solution. In order to improve adhesion of those materials, Ar plasma induced grafting is used to create hydrophilic surfaces of up to 40 μm. Hydrophilic PVDF-graft-polyethylene glycol allows diffusion of PEDOT/PSS in the pores of the membranes, while hydrophobic middle layers prevent short circuits. In this way, soft actuators can be fabricated by consequent drop casting and drying of conducting polymer.