Human behaviors are extremely sophisticated, relying on the adaptive, plastic and event-driven network of sensory neurons. Such neuronal system analyzes multiple sensory cues efficiently to establish accurate depiction of the environment. Here, we develop a bimodal artificial sensory neuron to implement the sensory fusion processes. Such a bimodal artificial sensory neuron collects optic and pressure information from the photodetector and pressure sensors respectively, transmits the bimodal information through an ionic cable, and integrates them into post-synaptic currents by a synaptic transistor. The sensory neuron can be excited in multiple levels by synchronizing the two sensory cues, which enables the manipulating of skeletal myotubes and a robotic hand. Furthermore, enhanced recognition capability achieved on fused visual/haptic cues is confirmed by simulation of a multi-transparency pattern recognition task. Our biomimetic design has the potential to advance technologies in cyborg and neuromorphic systems by endowing them with supramodal perceptual capabilities.

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An artificial sensory neuron with visual-haptic fusion.

Accurately detecting a potential collision and triggering a timely escape response is critical in the field of robotics and autonomous vehicle safety. The lobula giant movement detector (LGMD) neuron in locusts can detect an approaching object and prevent collisions within a swarm of millions of locusts. This single neuronal cell performs nonlinear mathematical operations on visual stimuli to elicit an escape response with minimal energy expenditure. Collision avoidance models based on image processing algorithms have been implemented using analogue very-large-scale-integration designs, but none is as efficient as this neuron in terms of energy consumption or size. Here we report a nanoscale collision detector that mimics the escape response of the LGMD neuron. The detector comprises a monolayer molybdenum disulfide photodetector stacked on top of a non-volatile and programmable floating-gate memory architecture. It consumes a small amount of energy (in the range of nanojoules) and has a small device footprint (~1 µm × 5 µm). By integrating a MoS2 photodetector with a floating-gate memory device, a nanoscale collision detector can be created that mimics the escape response of the lobula giant movement detector neuron.

A low-power biomimetic collision detector based on an in-memory molybdenum disulfide photodetector

We challenged tethered, flying locusts with visual stimuli looming from the side towards one eye in a way that mimics the approach of a predatory bird. Locusts respond to the lateral approach of a looming object with steering movements and a stereotyped, rapid behaviour in which the wingbeat pattern ceases and the wings are swept into a gliding posture. This gliding behaviour may cause the locust to dive. The gliding posture is maintained for 200 ms or more after which flight is resumed with an increased wingbeat frequency or else the wings are folded. A glide begins with a strong burst of activity in the mesothoracic second tergosternal motor neuron (no. 84) on both sides of the locust. Recordings of descending contralateral movement detector (DCMD) activity in a flying locust show that it responds to small (80-mm diameter) looming stimuli during tethered flight, with a prolonged burst of spikes that tracks stimulus approach and reaches peak instantaneous frequencies as, or after, stimulus motion ceases. There is a close match between the visual stimuli that elicit a gliding behaviour and those that are effective at exciting the DCMD neuron. Wing elevation into the gliding posture occurs during a maintained burst of high frequency DCMD spikes.

Gliding behaviour elicited by lateral looming stimuli in flying locusts A Neuroethology, sensory, neural, and behavioral physiology

Robotic swarms that take inspiration from nature are becoming a fascinating topic for multi-robot researchers. The aim is to control a large number of simple robots enables them in order to solve common complex tasks. Due to the hardware complexities and cost of robot platforms, current research in swarm robotics is mostly performed by simulation software. Simulation of large numbers of these robots which are used in swarm robotic applications is extremely complex and often inaccurate due to poor modelling of external conditions. In this paper we present the design of a low-cost, open-platform, autonomous micro robot (Colias) for swarm robotic applications. Colias employs a circular platform with a diameter of 4 cm. It has a maximum speed of 35 cm/s that gives the ability to be used in swarm scenarios very quickly in large arenas. Long-range infrared modules with adjustable output power allow the robot to communicate with its direct neighbours from a range of 0.5 cm to 3 m. Colias has been designed as a complete platform with supporting software development tools for robotics education and research. It has been tested in individual and swarm scenarios and the observed results demonstrate its feasibility to be used as a micro sized mobile robot as well as a low-cost platform for robot swarm applications.

https://journals.sagepub.com/doi/pdf/10.5772/58730

Matthais S. Keil

Papers

A bio-inspired visual collision detection mechanism for cars: Optimisation of a model of a locust neuron to a novel environment