Bipedal walking and push recovery with a stepping strategy based on time-projection control

In this paper, we present a simple control framework for online push recovery on biped robots with dynamic stepping properties. Owing to relatively heavy legs in our humanoid robot COMAN, we use a linear model called 3LP, which is composed of three pendulums to take swing and torso dynamics into account. Based on 3LP equations, we formulate discrete linear quadratic regulator (LQR) controllers and use a particular time-projection method to adjust footstep locations during the motion continuously. This process, which is based on pelvis and swing foot tracking errors, naturally considers swing dynamics and leads to leg-retraction properties. Suggested adjustments are added to the Cartesian 3LP gaits and converted into joint-space trajectories through inverse kinematics. Fixed and adaptive foot lift strategies are also used to ensure enough ground clearance in perturbed walking conditions. The proposed control architecture is robust, yet uses very simple state estimation and basic position tracking. We rely on series elastic actuators to absorb impacts while introducing simple laws to compensate for spring compressions. Extensive experiments on COMAN (real) and Atlas (simulated) robots demonstrate the functionality of different control blocks and prove the effectiveness of time-projection in extreme push recovery scenarios. We also show self-produced and emergent walking gaits when the robot is subject to continuous dragging forces. These gaits feature dynamic walking robustness with minimal reliance on the ankles and avoiding any active zero moment point (ZMP) control. The proposed architecture is therefore generic, computationally very fast and yet with no critical parameter to tune.

Push recovery with stepping strategy based on time-projection control

Salman Faraji, Auke Ijspeert, Seyed Hamed Razavi

In this paper, we present a simple control framework for on-line push recovery with dynamic stepping properties. Due to relatively heavy legs in our robot, we need to take swing dynamics into account and thus use a linear model called 3LP which is composed of three pendulums to simulate swing and torso dynamics. Based on 3LP equations, we formulate discrete LQR controllers and use a particular time-projection method to adjust the next footstep location on-line during the motion continuously. This adjustment, which is found based on both pelvis and swing foot tracking errors, naturally takes the swing dynamics into account. Suggested adjustments are added to the Cartesian 3LP gaits and converted to joint-space trajectories through inverse kinematics. Fixed and adaptive foot lift strategies also ensure enough ground clearance in perturbed walking conditions. The proposed structure is robust, yet uses very simple state estimation and basic position tracking. We rely on the physical series elastic actuators to absorb impacts while introducing simple laws to compensate their tracking bias. Extensive experiments demonstrate the functionality of different control blocks and prove the effectiveness of time-projection in extreme push recovery scenarios. We also show self-produced and emergent walking gaits when the robot is subject to continuous dragging forces. These gaits feature dynamic walking robustness due to relatively soft springs in the ankles and avoiding any Zero Moment Point (ZMP) control in our proposed architecture.

2018

Towards Robust Bipedal Locomotion

Salman Faraji

Thanks to better actuator technologies and control algorithms, humanoid robots to date can perform a wide range of locomotion activities outside lab environments. These robots face various control challenges like high dimensionality, contact switches during locomotion and a floating-base nature which makes them fall all the time. A rich set of sensory inputs and a high-bandwidth actuation are often needed to ensure fast and effective reactions to unforeseen conditions, e.g., terrain variations, external pushes, slippages, unknown payloads, etc. State of the art technologies today seem to provide such valuable hardware components. However, regarding software, there is plenty of room for improvement. Locomotion planning and control problems are often treated separately in conventional humanoid control algorithms. The control challenges mentioned above are probably the main reason for such separation. Here, planning refers to the process of finding consistent open-loop trajectories, which may take arbitrarily long computations off-line. Control, on the other hand, should be done very fast online to ensure stability. In this thesis, we want to link planning and control problems again and enable for online trajectory modification in a meaningful way. First, we propose a new way of describing robot geometries like molecules which breaks the complexity of conventional models. We use this technique and derive a planning algorithm that is fast enough to be used online for multi-contact motion planning. Similarly, we derive 3LP, a simplified linear three-mass model for bipedal walking, which offers orders of magnitude faster computations than full mechanical models. Next, we focus more on walking and use the 3LP model to formulate online control algorithms based on the foot-stepping strategy. The method is based on model predictive control, however, we also propose a faster controller with time-projection that demonstrates a close performance without numerical optimizations. We also deploy an efficient implementation of inverse dynamics together with advanced sensor fusion and actuator control algorithms to ensure a precise and compliant tracking of the simplified 3LP trajectories. Extensive simulations and hardware experiments on COMAN robot demonstrate effectiveness and strengths of our method. This thesis goes beyond humanoid walking applications. We further use the developed modeling tools to analyze and understand principles of human locomotion. Our 3LP model can describe the exchange of energy between human limbs in walking to some extent. We use this property to propose a metabolic-cost model of human walking which successfully describes trends in various conditions. The intrinsic power of the 3LP model to generate walking gaits in all these conditions makes it a handy solution for walking control and gait analysis, despite being yet a simplified model. To fill the reality gap, finally, we propose a kinematic conversion method that takes 3LP trajectories as input and generates more human-like postures. Using this method, the 3LP model, and the time-projecting controller, we introduce a graphical user interface in the end to simulate periodic and transient human-like walking conditions. We hope to use this combination in future to produce faster and more human-like walking gaits, possibly with more capable humanoid robots.

EPFL2018

Active origami platforms for human-robot interactions

Frédéric Henri Vaskin Giraud

Robots are employed to assist humans in lengthy, challenging, and repetitive tasks. However, the fields of rehabilitation, haptics, and assistive robotics have shown a significant need to support and interact with people in their everyday life. To facilitate these further needs, robots must overcome constraints in compactness, degrees of freedom (DoF), and mechanical performance. However, developing a robot with these characteristics is challenging for conventional mechanics. First, creating a meso-scale device requires the assembly of small components, which is laborious and increases manufacturing cost, time, and complexity. In addition, devices with several DoF and functionalities also require more parts to create numerous links and joints, actuators, and thus space, affecting the compactness of systems. Finally, aiming for mechanical performance in terms of force, speed, and motion range requires transmissions or bulky actuators, which also influence the size of the system. This thesis attempts to overcome the limitations of conventional mechanics by using origami robots, an alternative design approach for creating meso-scale structures with numerous folding joints. It consists in stacking layers of functional material to achieve low-profile and scalable structures that fold into 3D. Using this method, we developed three hybrid robots combining the decades of experience of conventional mechanics with the advantages of origami robotics. First, to enhance the performances of robots at the meso-scale, the creation of compact low-profile compliant transmissions benefiting from origami's minimal assembly of functional layers was explored. The transmissions obtained can reproduce conventional kinematics or generate unconventional motions using materials properties. Second, the development of multi-DoF compact robots was studied using the aforementioned low-profile compliant transmissions to create a multi-functional structure. The resulting robot is a fingertip haptic device called Haptigami that can render vibrotactile and three-DoF force feedback without compromising bulkiness. Then, this study aimed at creating a meso-scale, multi-DoF, and mechanically efficient robot. We combined the previous device contributions and developed Flexure Variable Stiffness Actuators (F-VSA), a novel compliant actuator that uses the origami flexure hinges' inherent stiffness to avoid hindering mechanical simplicity. Finally, we developed a software architecture that enables high-level control of the human-robot hardware and is compatible with multiple simulation engines. We used this architecture to control our robots and provide feedback to the user, based on interactions in a virtual environment. These novel robots rely on non-conventional structures, actuators, and kinematics that require exploring and testing suitable control strategies. Hence, kinematic and stiffness models were developed and used to tune the position, force, and stiffness of the end-effector. Several characterization platforms and experimental protocols suitable for testing our unique robotic systems were also developed to assess their precision and efficiency. Consequently, the results of this study pave the way for the development of robots that adapt to multiple environments, interactions, and application scenarios, compatible with the human bandwidth without hindering the user's motion and comfort in everyday life.