A physical model of sensorimotor interactions during locomotion

Klein, Theresa J.; Lewis, M. Anthony

doi:10.1088/1741-2560/9/4/046011

Cited by 20 publications

(22 citation statements)

References 54 publications

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“…Our work reaffirms the work by Klein and Lewis (2012) that dynamic neural systems are affective tools for controlling dynamic walking systems. Our work expands upon this by implementing a more detailed model of intra-leg sensory pathways and demonstrates that the proposed mechanisms are effective for regulating stance and swing timing, as well as muscle force production for forward walking by adapting each step individually.…”

Section: Discussionsupporting

confidence: 86%

“…Inclusion of these sensors in the walking control system would add redundancy to ground detection and would likely result in more stable behaviors. These could act as ground contact sensors, similar to those used in Klein and Lewis (2012). …”

Section: Discussionmentioning

confidence: 99%

“…OCTAVIO uses an artificial neural network assembled from modular subnetworks, much like the work we present in this paper (von Twickel et al, 2011). The biped built by Klein and Lewis and Redbot both demonstrated how a spiking neural network can be used to produce locomotion in a biped robot (Klein and Lewis, 2012). These robots have controllers that mimic the logic and structure of the animal's nervous systems, and as such, serve as tools for investigating neurobiological hypotheses, however, all these controllers were developed by hand tuning parameter values, and are limited by the engineer's ability to calibrate the system.…”

Section: Introductionmentioning

confidence: 99%

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Development and Training of a Neural Controller for Hind Leg Walking in a Dog Robot

2017

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Animals dynamically adapt to varying terrain and small perturbations with remarkable ease. These adaptations arise from complex interactions between the environment and biomechanical and neural components of the animal's body and nervous system. Research into mammalian locomotion has resulted in several neural and neuro-mechanical models, some of which have been tested in simulation, but few “synthetic nervous systems” have been implemented in physical hardware models of animal systems. One reason is that the implementation into a physical system is not straightforward. For example, it is difficult to make robotic actuators and sensors that model those in the animal. Therefore, even if the sensorimotor circuits were known in great detail, those parameters would not be applicable and new parameter values must be found for the network in the robotic model of the animal. This manuscript demonstrates an automatic method for setting parameter values in a synthetic nervous system composed of non-spiking leaky integrator neuron models. This method works by first using a model of the system to determine required motor neuron activations to produce stable walking. Parameters in the neural system are then tuned systematically such that it produces similar activations to the desired pattern determined using expected sensory feedback. We demonstrate that the developed method successfully produces adaptive locomotion in the rear legs of a dog-like robot actuated by artificial muscles. Furthermore, the results support the validity of current models of mammalian locomotion. This research will serve as a basis for testing more complex locomotion controllers and for testing specific sensory pathways and biomechanical designs. Additionally, the developed method can be used to automatically adapt the neural controller for different mechanical designs such that it could be used to control different robotic systems.

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Section: Discussionsupporting

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Development and Training of a Neural Controller for Hind Leg Walking in a Dog Robot

2017

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“…For gait, these synergies are well-established (Ivanenko et al, 2005) and they have been shown to be robust in a wide variety of gait conditions (Ivanenko et al, 2004, 2006a,b, 2007). In fact, it is now possible to use these synergies to model human gait (see below) and in the future it is conceivable that these new notions enter the field of robotics, since there is increasing interest to incorporate physiological features in the design of walking robots (Klein and Lewis, 2012). …”

Section: Acting Against Gravity: Extensor Synergies In the Spinal Cordmentioning

confidence: 99%

The flexion synergy, mother of all synergies and father of new models of gait

Duysens¹,

Groote²,

Jonkers³

2013

Front. Comput. Neurosci.

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Recently there has been a growing interest in the modular organization of leg movements, in particular those related to locomotion. One of the basic modules involves the flexion of the leg during swing and it was shown that this module is already present in neonates (Dominici et al., 2011). In this paper, we question how these finding build upon the original work by Sherrington, who proposed that the flexor reflex is the basic building block of flexion during swing phase. Similarly, the relation between the flexor reflex and the withdrawal reflex modules of Schouenborg and Weng (1994) will be discussed. It will be argued that there is large overlap between these notions on modules and the older concepts of reflexes. In addition, it will be shown that there is a great flexibility in the expression of some of these modules during gait, thereby allowing for a phase-dependent modulation of the appropriate responses. In particular, the end of the stance phase is a period when the flexor synergy is facilitated. It is proposed that this is linked to the activation of circuitry that is responsible for the generation of locomotor patterns (CPG, “central pattern generator”). More specifically, it is suggested that the responses in that period relate to the activation of a flexor burst generator. The latter structure forms the core of a new asymmetric model of the CPG. This activation is controlled by afferent input (facilitation by a broad range of afferents, suppression by load afferent input). Meanwhile, many of these physiologic features have found their way in the control of very flexible walking bipedal robots.

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“…Some projects were carried comprising CPGs and reflexes (Kimura et al, 2007;Wadden and Ekeberg, 1998;Maufroy et al, 2008;Ekeberg and Pearson, 2005;Klein and Lewis, 2012). In all these studies, CPGs are the central mechanism responsible for direct motor generation, and reflexes had the function of regulating/modifying the CPG's activity.…”

Section: Overview Of the Researchmentioning

confidence: 99%

Robotic locomotion combining Central Pattern Generators and reflexes

Ferreira

Santos

2015

2015 IEEE 4th Portuguese Meeting on Bioengineering (ENBENG)

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All the work carried during the past year would not be possible without the help, understanding and support from many people. First and foremost, I would like to express my deepest gratitude to my adviser Prof. Cristina Santos, who allowed me the possibility to integrate the CAR (Control, Automation and Robotics) group of the ALGORITMI center. I am extremely grateful for her dedication, support and constant motivation, providing me an excellent atmosphere to complete my thesis. I am sincerely grateful for her excellent guidance and perseverance, encouraging me to tackle the different problems of this research. The help, constructive criticism and advice that I received were invaluable to the final quality of this work, making suggestions that contributed to overcoming the difficulties that emerged during this journey. I would like to thank Prof. Lino Costa for the opportunity to learn new topics related with fitness evaluation. I want to express my gratitude to Prof. Auke Ijspeert, who was always available to help with whatever was needed, provided insighful discussions about the research and presented suggestions that helped me develop this accomplishment. I am especially thankful to everybody in the lab, for all the friendship and companionship that provided me with an excellent daily environment. A special thanks to João Macedo, who was always available to help me solve computational issues. I express my warm thank you to my girlfriend Bárbara for her support, dedication and patience during the last year. She assisted me when I was writing this thesis, giving me some insight to stay on track and complete this work successfully. Finally, I would like to thank my family, my parents and my brother, for their constant support, love and encouragement.

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A physical model of sensorimotor interactions during locomotion

Cited by 20 publications

References 54 publications

Development and Training of a Neural Controller for Hind Leg Walking in a Dog Robot

Development and Training of a Neural Controller for Hind Leg Walking in a Dog Robot

The flexion synergy, mother of all synergies and father of new models of gait

Robotic locomotion combining Central Pattern Generators and reflexes

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