Emergence of robust self-organized undulatory swimming based on local hydrodynamic force sensing

Undulatory swimming represents an ideal behavior to investigate locomotion control and the role of the underlying central and peripheral components in the spinal cord. Many vertebrate swimmers have central pattern generators and local pressure-sensitive receptors that provide information about the surrounding fluid. However, it remains difficult to study experimentally how these sensors influence motor commands in these animals. Here, using a specifically designed robot that captures the essential components of the animal neuromechanical system and using simulations, we tested the hypothesis that sensed hydrodynamic pressure forces can entrain body actuation through local feedback loops. We found evidence that this peripheral mechanism leads to self-organized undulatory swimming by providing intersegmental coordination and body oscillations. Swimming can be redundantly induced by central mechanisms, and we show that, therefore, a combination of both central and peripheral mechanisms offers a higher robustness against neural disruptions than any of them alone, which potentially explains how some vertebrates retain locomotor capabilities after spinal cord lesions. These results broaden our understanding of animal locomotion and expand our knowledge for the design of robust and modular robots that physically interact with the environment.

Neuroprosthetic rehabilitation and translational mechanism after severe spinal cord injury

Lucia Florinda Friedli Wittler

Traumatic SCIs have long-term health, economic and social consequences, stressing the urgency to develop interventions to improve recovery after such injuries. Today, the only proven effective interventions to enhance recovery after SCI are activity-based rehabilitation therapies, such as locomotor training. However, locomotor training shows no or very limited efficacy to improve function after a severe SCI that induces paralysis of the limbs. To mimic the outcome of severe but incomplete SCI in rodents, we developed a model of double opposite-side lateral hemisections termed staggered hemisection in adult rats. This model induced permanent paralysis below the level of injury but leaves an intervening gap of intact neural tissue that provides a substrate for recovery. We showed that this SCI leads to degradation of motor functions, which correlates with the formation of aberrant neuronal connections below the lesion. Robotic devices with a rehabilitative purpose should act as propulsive or postural neuroprosthesis allowing training under natural conditions. Our versatile robotic interface provides multidirectional bodyweight support during overground locomotion in rats. We next evaluated the effects of robot-assisted gait training enabled by electrochemical stimulation of spinal circuits to restore locomotion after staggered hemisection SCI. We found that after two months of daily training, paralyzed rats recovered the ability to initiate, sustain and adjust bipedal locomotion while supported in the robot under electrochemical stimulation. This recovery correlated with ubiquitous reorganization of corticospinal, brainstem, and intraspinal fibers. We next evaluated whether this treatment was capable of restoring supraspinal control of locomotion after a clinically relevant SCI. Rats received a severe contusion of the spinal cord that spared less than 10% of intact tissue. Robot-assisted rehabilitation restored weight-bearing locomotion in all the trained rats when stimulated electrochemicallay and in a subset of rats in the absence of any enabling factors which paralelled with the reorganization of axonal projections of reticulospinal fibers below the contusion. Virus-mediated silencing of reticulospinal neurons projecting to lumbar segments demonstrated that these inputs were necessary to initiate and sustain walking after training. When delaying the onset of training by two months, in the chronic stage, all the rats regained voluntary locomotor movements but the extent of the recovery was reduced compared to rats trained early after SCI. The results provide a strong rationale to evaluate the impact of neuroprosthetic training to improve motor functions in human patients with incomplete SCI. Translation of treatment paradigms developed in rodent models into effective clinical applications remains a major challenge in biomedical research. Here, we studied recovery of motor functions in more than 400 quadriplegic patients who presented various degree of spinal cord damage laterality. We found that recovery increases with the asymmetry of early motor deficits. We conclude that emergence of spinal cord decussating corticospinal fibers and bilateral motor cortex projections during mammalian evolution supports greater recovery after lateralized SCI primates compared to rodents. Novel experimental models and dedicated therapeutic strategies are necessary to take advantage of this powerful neuronal substrate for recovery after SCI.

EPFL2014

Roombots: Reconfigurable Robots for Adaptive Furniture

Aude Billard, Stéphane Bonardi, Pierre Dillenbourg, Auke Ijspeert, Rico Möckel, Soha Pouya, Alexander Spröwitz, Jesse van den Kieboom

Imagine a world in which our furniture moves around like legged robots, interacts with us, and changes shape and function during the day according to our needs. This is the long term vision we have in the Roombots project. To work towards this dream, we are developing modular robotic modules that have rotational degrees of freedom for locomotion as well as active connection mechanisms for runtime reconfiguration. A piece of furniture, e.g. a stool, will thus be composed of several modules that activate their rotational joints together to implement locomotor gaits, and will be able to change shape, e.g. transforming into a chair, by sequences of attachments and detachments of modules. In this article, we firstly present the project and the hardware we are currently developing. We explore how reconfiguration from a configuration A to a configuration B can be controlled in a distributed fashion. This is done using metamodules-two Roombots modules connected serially-that use broadcast signals and connections to a structured ground to collectively build desired structures without the need of a centralized planner. We then present how locomotion controllers can be implemented in a distributed system of coupled oscillators-one per degree of freedom-similarly to the concept of central pattern generators (CPGs) found in the spinal cord of vertebrate animals. The CPGs are based on coupled phase oscillators to ensure synchronized behavior and have different output filters to allow switching between oscillations and rotations. A stochastic optimization algorithm is used to explore optimal CPG configurations for different simulated Roombots structures.

2010

Rich and Robust Bio-Inspired Locomotion Control for Humanoid Robots

Nicolas Benoît Dominique Van der Noot

Bipedal locomotion is a challenging task in the sense that it requires to maintain dynamic balance while steering the gait in potentially complex environments. Yet, humans usually manage to move without any apparent difficulty, even on rough terrains. This requires a complex control scheme which is far from being understood. In this thesis, we take inspiration from the impressive human walking capabilities to design neuromuscular controllers for humanoid robots. More precisely, we control the robot motors to reproduce the action of virtual muscles commanded by stimulations (i.e. neural signals), similarly to what is done during human locomotion. Because the human neural circuitry commanding these muscles is not completely known, we make hypotheses about this control scheme to simplify it and progressively refine the corresponding rules. This thesis thus aims at developing new walking algorithms for humanoid robots in order to obtain fast, human-like and energetically efficient gaits. In particular, gait robustness and richness are two key aspects of this work. In other words, the gaits developed in the thesis can be steered by an external operator, while being resistant to external perturbations. This is mainly tested during blind walking experiments on COMAN, a 95 cm tall humanoid robot. Yet, the proposed controllers can be adapted to other humanoid robots. In the beginning of this thesis, we adapt and port an existing reflex-based neuromuscular model to the real COMAN platform. When tested in a 2D simulation environment, this model was capable of reproducing stable human-like locomotion. By porting it to real hardware, we show that these neuromuscular controllers are viable solutions to develop new controllers for robotics locomotion. Starting from this reflex-based model, we progressively iterate and transform the stimulation rules to add new features. In particular, gait modulation is obtained with the inclusion of a central pattern generator (CPG), a neural circuit capable of producing rhythmic patterns of neural activity without receiving rhythmic inputs. Using this CPG, the 2D walker controllers are incremented to generate gaits across a range of forward speeds close to the normal human one. By using a similar control method, we also obtain 2D running gaits whose speed can be controlled by a human operator. The walking controllers are later extended to 3D scenarios (i.e. no motion constraint) with the capability to adapt both the forward speed and the heading direction (including steering curvature). In parallel, we also develop a method to automatically learn stimulation networks for a given task and we study how flexible feet affect the gait in terms of robustness and energy efficiency. In sum, we develop neuromuscular controllers generating human-like gaits with steering capabilities. These controllers recruit three main components: (i) virtual muscles generating torque references at the joint level, (ii) neural signals commanding these muscles with reflexes and CPG signals, and (iii) higher level commands controlling speed and heading. Interestingly, these developments target humanoid robots locomotion but can also be used to better understand human locomotion. In particular, the recruitment of a CPG during human locomotion is still a matter open to debate. This question can thus benefit from the experiments performed in this thesis.