skip to main content


Title: A perspective on the neuromorphic control of legged locomotion in past, present, and future insect-like robots
Abstract

This article is a historical perspective on how the study of the neuromechanics of insects and other arthropods has inspired the construction, and especially the control, of hexapod robots. Many hexapod robots’ control systems share common features, including: 1. Direction of motor output of each joint (i.e. to flex or extend) in the leg is gated by an oscillatory or bistable gating mechanism; 2. The relative phasing between each joint is influenced by proprioceptive feedback from the periphery (e.g. joint angles, leg load) or central connections between joint controllers; and 3. Behavior can be directed (e.g. transition from walking along a straight path to walking along a curve) via low-dimensional, broadly-acting descending inputs to the network. These distributed control schemes are inspired by, and in some robots, closely mimic the organization of the nervous systems of insects, the natural hexapods, as well as crustaceans. Nearly a century of research has revealed organizational principles such as central pattern generators, the role of proprioceptive feedback in control, and command neurons. These concepts have inspired the control systems of hexapod robots in the past, in which these structures were applied to robot controllers with neuromorphic (i.e. distributed) organization, but not neuromorphic computational units (i.e. neurons) or computational hardware (i.e. hardware-accelerated neurons). Presently, several hexapod robots are controlled with neuromorphic computational units with or without neuromorphic organization, almost always without neuromorphic hardware. In the near future, we expect to see hexapod robots whose controllers include neuromorphic organization, computational units, and hardware. Such robots may exhibit the full mobility of their insect counterparts thanks to a ‘biology-first’ approach to controller design. This perspective article is not a comprehensive review of the neuroscientific literature but is meant to give those with engineering backgrounds a gentle introduction into the neuroscientific principles that underlie models and inspire neuromorphic robot controllers. A historical summary of hexapod robots whose control systems and behaviors use neuromorphic elements is provided. Robots whose controllers closely model animals and may be used to generate concrete hypotheses for future animal experiments are of particular interest to the authors. The authors hope that by highlighting the decades of experimental research that has led to today’s accepted organization principles of arthropod nervous systems, engineers may better understand these systems and more fully apply biological details in their robots. To assist the interested reader, deeper reviews of particular topics from biology are suggested throughout.

 
more » « less
Award ID(s):
2015317 1704436
NSF-PAR ID:
10405619
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
IOP Publishing
Date Published:
Journal Name:
Neuromorphic Computing and Engineering
Volume:
3
Issue:
2
ISSN:
2634-4386
Page Range / eLocation ID:
Article No. 023001
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. This article is a historical perspective on how the study of the neuromechanics of insects and other arthropods has inspired the construction, and especially the control, of hexapod robots. Many hexapod robots’ control systems share common features, including: 1. Direction of motor output of each joint (i.e. to flex or extend) in the leg is gated by an oscillatory or bistable gating mechanism; 2. The relative phasing between each joint is influenced by proprioceptive feedback from the periphery (e.g. joint angles, leg load) or central connections between joint controllers; and 3. Behavior can be directed (e.g. transition from walking along a straight path to walking along a curve) via low-dimensional, broadly-acting descending inputs to the network. These distributed control schemes are inspired by, and in some robots, closely mimic the organization of the nervous systems of insects, the natural hexapods, as well as crustaceans. Nearly a century of research has revealed organizational principles such as central pattern generators, the role of proprioceptive feedback in control, and command neurons. These concepts have inspired the control systems of hexapod robots in the past, in which these structures were applied to robot controllers with neuromorphic (i.e. distributed) organization, but not neuromorphic computational units (i.e. neurons) or computational hardware (i.e. hardware-accelerated neurons). Presently, several hexapod robots are controlled with neuromorphic computational units with or without neuromorphic organization, almost always without neuromorphic hardware. In the near future, we expect to see hexapod robots whose controllers include neuromorphic organization, computational units, and hardware. Such robots may exhibit the full mobility of their insect counterparts thanks to a ‘biology-first’ approach to controller design. This perspective article is not a comprehensive review of the neuroscientific literature but is meant to give those with engineering backgrounds a gentle introduction into the neuroscientific principles that underlie models and inspire neuromorphic robot controllers. A historical summary of hexapod robots whose control systems and behaviors use neuromorphic elements is provided. Robots whose controllers closely model animals and may be used to generate concrete hypotheses for future animal experiments are of particular interest to the authors. The authors hope that by highlighting the decades of experimental research that has led to today’s accepted organization principles of arthropod nervous systems, engineers may better understand these systems and more fully apply biological details in their robots. To assist the interested reader, deeper reviews of particular topics from biology are suggested throughout. 
    more » « less
  2. Abstract

    Many invertebrates are ideal model systems on which to base robot design principles due to their success in solving seemingly complex tasks across domains while possessing smaller nervous systems than vertebrates. Three areas are particularly relevant for robot designers: Research on flying and crawling invertebrates has inspired new materials and geometries from which robot bodies (their morphologies) can be constructed, enabling a new generation of softer, smaller, and lighter robots. Research on walking insects has informed the design of new systems for controlling robot bodies (their motion control) and adapting their motion to their environment without costly computational methods. And research combining wet and computational neuroscience with robotic validation methods has revealed the structure and function of core circuits in the insect brain responsible for the navigation and swarming capabilities (their mental faculties) displayed by foraging insects. The last decade has seen significant progress in the application of principles extracted from invertebrates, as well as the application of biomimetic robots to model and better understand how animals function. This Perspectives paper on the past 10 years of the Living Machines conference outlines some of the most exciting recent advances in each of these fields before outlining lessons gleaned and the outlook for the next decade of invertebrate robotic research.

     
    more » « less
  3. We present simplified 2D dynamic models of the 3D, passive dynamic inspired walking gait of a physical quasi-passive walking robot. Quasi-passive walkers are robots that integrate passive walking principles and some form of actuation. Our ultimate goal is to better understand the dynamics of actuated walking in order to create miniature, untethered, bipedal walking robots. At these smaller scales there is limited space and power available, and so in this work we leverage the passive dynamics of walking to reduce the burden on the actuators and controllers. Prior quasi-passive walkers are much larger than our intended scale, have more complicated mechanical designs, and require more precise feedback control and/or learning algorithms. By leveraging the passive 3D dynamics, carefully designing the spherical feet, and changing the actuation scheme, we are able to produce a very simple 3D bipedal walking model that has a total of 5 rigid bodies and a single actuator per leg. Additionally, the model requires no feedback as each actuator is controlled by an open-loop sinusoidal profile. We validate this model in 2D simulations in which we measure the stability properties while varying the leg length/amplitude ratio, the frequency of actuation, and the spherical foot profile. These results are also validated experimentally on a 3D walking robot (15cm leg length) that implements the modeled walking dynamics. Finally, we experimentally investigate the ability to control the heading of the robot by changing the open-loop control parameters of the robot. 
    more » « less
  4. Hunt, Alexander ; Vouloutsi, Vasiliki ; Moses, Kenneth ; Quinn, Roger ; Mura, Anna ; Prescott, Tony ; Verschure, Paul F. (Ed.)
    Load sensing is critical for walking behavior in animals, who have evolved a number of sensory organs and neural systems to improve their agility. In particular, insects measure load on their legs using campaniform sensilla (CS), sensory neurons in the cuticle of high-stress portions of the leg. Extracellular recordings from these sensors in a behaving animal are difficult to collect due to interference from muscle potentials, and some CS groups are largely inaccessible due to their placement on the leg. To better understand what loads the insect leg experiences and what sensory feedback the nervous system may receive during walking, we constructed a dynamically-scaled robotic model of the leg of the stick insect Carausius morosus. We affixed strain gauges in the same positions and orientations as the major CS groups on the leg, i.e., 3, 4, 6A, and 6B. The robotic leg was mounted to a vertically-sliding linear guide and stepped on a treadmill to simulate walking. Data from the strain gauges was run through a dynamic model of CS discharge developed in a previous study. Our experiments reveal stereotypical loading patterns experienced by the leg, even as its weight and joint stiffness is altered. Furthermore, our simulated CS strongly signal the beginning and end of stance phase, two key events in the coordination of walking. 
    more » « less
  5. : Inspired by the locomotor nervous system of vertebrates, central pattern generator (CPG) models can be used to design gaits for articulated robots, such as crawling, swimming or legged robots. Incorporating sensory feedback for gait adaptation in these models can improve the locomotive performance of such robots in challenging terrain. However, many CPG models to date have been developed exclusively for open-loop gait generation for traversing level terrain. In this paper, we present a novel approach for incorporating inertial feedback into the CPG framework for the control of body posture during legged locomotion on steep, unstructured terrain. That is, we adapt the limit cycle of each leg of the robot with time to simultaneously produce locomotion and body posture control. We experimentally validate our approach on a hexapod robot, locomoting in a variety of steep, challenging terrains (grass, rocky slide, stairs). We show how our approach can be used to level the robot's body, allowing it to locomote at a relatively constant speed, even as terrain steepness and complexity prevents the use of an open-loop control strategy. 
    more » « less