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 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., walking along a curved path) 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 (CPGs), 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 is not a comprehensive review of the neuroscientific literature but is meant to give a gentle introduction into the principles that underlie models and inspire neuromorphic robot controllers. Deeper reviews of particular topics from biology are suggested throughout.

Qualitative switches in single-neuron spike dynamics on neuromorphic hardware: implementation, impact on network synchronization and relevance for plasticity

“…lamprey swimming control networks on SpiNNaker and Loihi [32]. The novel, direct and simple control of phase relations between neurons via a single cell-intrinsic parameter demonstrated here further enriches the repertoire of emulating insect and other resource-efficient neural systems for neuro-robotics [33,34] or edge processing [35].…”

Mechanical modeling of mechanosensitive insect strain sensors as a tool to investigate exoskeletal interfaces

“…All elliptical CS had the largest microstrain values during left (CS 2, 6, 8) or right (3,7,9,10,11) loading.…”

“…For decades, continuing advances in research into the neurobiology of motor control and a biologyfirst approach to robotics have complemented each other [7]. This research has highlighted the benefits of utilizing sensory feedback systems for limb coordination as well as the robust benefits of using biomimicry in robotics.…”

A biomimetic fruit fly robot for studying the neuromechanics of legged locomotion

“…Insects have consistently been a target for bio-inspired and biomimetic legged robotics [reviews in [25], [26], [27], [28]]. Despite the small size of their bodies and nervous systems, insects demonstrate a range of legged behaviors rivaling that of vertebrates.…”