Auxetic Metamaterial Simplifies Soft Robot Design

Soft materials are being adopted in robotics in order to facilitate biomedical applications and in order to achieve simpler and more capable robots. One route to simplification is to design the robot's body using 'smart materials' that carry the burden of control and actuation. Metamaterials enable just such rational design of the material properties. Here we present a soft robot that exploits mechanical metamaterials for the intrinsic synchronization of two passive clutches which contact its travel surface. Doing so allows it to move through an enclosed passage with an inchworm motion propelled by a single actuator. Our soft robot consists of two 3D-printed metamaterials that implement auxetic and normal elastic properties. The design, fabrication and characterization of the metamaterials are described. In addition, a working soft robot is presented. Since the synchronization mechanism is a feature of the robot's material body, we believe that the proposed design will enable compliant and robust implementations that scale well with miniaturization.

Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform

Ugo Albanese, Alessandro Ambrosano, Nino Cauli, Oliver Denninger, Stefan Deser, Egidio Falotico, Marc-Oliver Gewaltig, Luc Guyot, Georg Hinkel, Murat Kirtay, Paul Levi, Patrick Maier, Daniel Peppicelli, Igor Peric, Eduardo Ros, Stefan Ulbrich, Patrick Van Der Smagt, Lorenzo Vannucci, Axel von Arnim, Sandro Weber

Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task. Rather, the embodiment has to be simulated as well. While adequate tools exist to simulate either complex neural networks or robots and their environments, there is so far no tool that allows to easily establish a communication between brain and body models. The Neurorobotics Platform is a new web-based environment that aims to fill this gap by offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in silico experimentation. In order to simplify the workflow and reduce the level of the required programming skills, the platform provides editors for the specification of experimental sequences and conditions, environments, robots, and brain-body connectors. In addition to that, a variety of existing robots and environments are provided. This work presents the architecture of the first release of the Neurorobotics Platform developed in subproject 10 "Neurorobotics" of the Human Brain Project (HBP). 1 At the current state, the Neurorobotics Platform allows researchers to design and run basic experiments in neurorobotics using simulated robots and simulated environments linked to simplified versions of brain models. We illustrate the capabilities of the platform with three example experiments: a Braitenberg task implemented on a mobile robot, a sensory-motor learning task based on a robotic controller, and a visual tracking embedding a retina model on the iCub humanoid robot. These use-cases allow to assess the applicability of the Neurorobotics Platform for robotic tasks as well as in neuroscientific experiments.

2017

Development of Essential Components for Soft Wearable Technologies

Amir Firouzeh

The rising demand for safe human-robot interaction in daily tasks has motivated significant research effort in the robotics field towards compliant and conformable robots, capable of replicating complex human movements in applications such as wearable rehabilitative devices and haptic interfaces. Novel manufacturing, actuation, and sensing technologies contributed significantly to this field by providing design and manufacturing frameworks for inherently compliant robots. Although promising, these technologies are still in the early stages of development and base research for refining their design, improving their performance, and defining design criteria is still required for these technologies to reach their full potential. In this thesis, some of the main challenges hindering the effective application of robotics in wearable devices are tackled. We propose the robotic origami (robogami) framework with multiple but finite degrees of freedom (DoFs) for soft wearable devices. Robogamis are low profile robots that provide conformity and compliance with their multiple DoFs driven by soft actuation methods. The finite DoFs in these robots enable better prediction and planning of their motion while highly customizable joint designs, thanks to the layer-by-layer manufacturing and the precise quasi-2D fabrication processes, allows the multiple DoFs to be embedded to achieve the required level of conformity. The main contributions of this thesis are: -Study of the robogami framework as a design platform for soft robots with programmable reconfiguration and compliance. -Design and validation of actuation solutions based on smart materials for independent actuation of robogami joints. -Adoption of the smart materials' variable mechanical properties to adjust the stiffness of robogami joints and the overall compliance of the robot. -Development of customized sensing methods to measure robogami joint angles and stretchable sensors based on the same principles to measure body movements. We believe that these contributions facilitate some of the main challenges for the effective application of robogamis in wearable devices for safe and yet capable interaction with humans. The highly customizable components can also be used in design frameworks other than robogamis and other applications where compliance and conformity are required.

EPFL2017

Hardware, software and control design considerations towards low-cost compliant quadruped robots

Alexandre Tuleu

Quadrupedal robots have been a field of interest the last few years, with many new maturing platforms. Many of these projects have in common the use of state of the art actuation and sensing, and therefore are able to handle difficult locomotion tasks very effectively. This work focuses on another trend of low-cost, quadrupedal robots, that features less precise actuators and sensors, but overcomes their limitations with strong bio-inspired designs to achieve state of the art locomotion. We aim here to further extend the achievements of this approach to handle more complex tasks and that require anticipation, We would like also to verify to which extent a close synergy between clever mechanics, sensorimotor coordination, and Central Pattern Generator models is able to handle these tasks. This thesis presents supporting work that was required to pursue this goal. A software architecture for the development of real-time drivers and low-level control for robotic applications, based on a clear separation of concerns is presented. An implementation of this architecture able to handle the specific requirements for small compliant quadruped robots is proposed. Furthermore, the development and integration of a communication protocol for inter-electronic devices communication on the Oncilla robot is discussed. As leg load is a key quantity in some of the sensory-motor coordination this thesis want to explore, a novel tactile sensing approach for its estimation is proposed, based on an Extended Kalman Filter data fusion of static and dynamic tactile sensor information. Then, to support the design of efficient interactions between the control and the bio-inspired mechanics, accurate dynamic modeling of the Advanced Spring Loaded Pantographic leg, equipping all robots considered here, is presented. We propose two approaches to this modeling with the presentation of their benefits and limitations. Finally, two Central Pattern Generator architectures are proposed, based on biologically inspired foot trajectories. The first is using a well-known method for inter-limb coordination with strong neural coupling, and the second, the Tegotae rule, relies only on limb physical coupling and strong sensory-motor coordination. These two approaches are compared on their capacity to handle dynamic footstep placement and it let to the conclusion that strong sensory-motor coordination is required for this task.

EPFL2016