Insect Navigation: What Backward Walking Reveals about the Control of Movement

Forward and backward control of an ultrafast millimeter-scale microrobot via vibration mode transition

The ability to move backward is crucial for millimeter-scale microrobots to navigate dead-end tunnels that are too narrow to allow for turning maneuvers. In this study, we introduce a 15-mm-long legged microrobot, BHMbot-B, which is capable of rapid forward and backward locomotion through vibration mode transition control. By properly arranging the vibratory motions of the magnet, cantilever, and linkages, the pitching movement of the body and the vibration of the forelegs are in phase during the first-order vibration mode of the cantilever and in antiphase during the second-order mode, which induces the forward and backward movement of the microrobot. Owing to its outstanding load-bearing capacity, the BHMbot-B equipped with dual electromagnetic actuators, an onboard battery, and a control circuit, can execute complex running trajectories under wireless command. Its maximum untethered running speeds are evaluated as 18.0 BL/s (360 mm/s) in the forward direction and 16.9 BL/s (338 mm/s) in the backward direction.

Postural Change of the Annual Cicada (Tibicen linnei) Helps Facilitate Backward Flight

Cicadas are heavy fliers well known for their life cycles and sound production; however, their flight capabilities have not been extensively investigated. Here, we show for the first time that cicadas appropriate backward flight for additional maneuverability. We studied this flight mode using computational fluid dynamics (CFD) simulations based on three-dimensional reconstructions of high-speed videos captured in a laboratory. Backward flight was characterized by steep body angles, high angles of attack, and high wing upstroke velocities. Wing motion occurred in an inclined stroke plane that was fixed relative to the body. Likewise, the directions of the half-stroke-averaged aerodynamic forces relative to the body (local frame) were constrained in a narrow range (<20°). Despite the drastic difference of approximately 90° in body posture between backward and forward flight in the global frame, the aerodynamic forces in both flight scenarios were maintained in a similar direction relative to the body. The forces relative to the body were also oriented in a similar direction when observed during climbs and turns, although the body orientation and motions were different. Hence, the steep posture appropriated during backward flight was primarily utilized for reorienting both the stroke plane and aerodynamic force in the global frame. A consequence of this reorientation was the reversal of aerodynamic functions of the half strokes in backward flight when compared to forward flight. The downstroke generated propulsive forces, while the upstroke generated vertical forces. For weight support, the upstroke, which typically generates lesser forces in forward flight, is aerodynamically active in backward flight. A leading-edge vortex (LEV) was observed on the forewings during both half strokes. The LEV's effect, together with the high upstroke velocity, increased the upstroke's force contribution from 10% of the net forces in forward flight to 50% in backward flight. The findings presented in this study have relevance to the design of micro-aerial vehicles (MAVs), as backward flight is an important characteristic for MAV maneuverability or for taking off from vertical surfaces.

No Need for Landmarks: An Embodied Neural Controller for Robust Insect-Like Navigation Behaviors

Bayesian filters have been considered to help refine and develop theoretical views on spatial cell functions for self-localization. However, extending a Bayesian filter to reproduce insect-like navigation behaviors (e.g., home searching) remains an open and challenging problem. To address this problem, we propose an embodied neural controller for self-localization, foraging, backward homing (BH), and home searching of an advanced mobility sensor (AMOS)-driven insect-like robot. The controller, comprising a navigation module for the Bayesian self-localization and goal-directed control of AMOS and a locomotion module for coordinating the 18 joints of AMOS, leads to its robust insect-like navigation behaviors. As a result, the proposed controller enables AMOS to perform robust foraging, BH, and home searching against various levels of sensory noise, compared to conventional controllers. Its implementation relies only on self-localization and heading perception, rather than global positioning and landmark guidance. Interestingly, the proposed controller makes AMOS achieve spiral searching patterns comparable to those performed by real insects. We also demonstrated the performance of the controller for real-time indoor and outdoor navigation in a real insect-like robot without any landmark and cognitive map.

Towards a multi-level understanding in insect navigation

To understand the brain is to understand behaviour. However, understanding behaviour itself requires consideration of sensory information, body movements and the animal's ecology. Therefore, understanding the link between neurons and behaviour is a multi-level problem, which can be achieved when considering Marr's three levels of understanding: behaviour, computation, and neural implementation. Rather than establishing direct links between neurons and behaviour, the matter boils down to understanding two transitions: the link between neurons and brain computation on one hand, and the link between brain computations and behaviour on the other hand. The field of insect navigation illustrates well the power of such two-sided endeavour. We provide here examples revealing that each transition requires its own approach with its own intrinsic difficulties, and show how modelling can help us reach the desired multi-level understanding.

Route-following ants respond to alterations of the view sequence

Ants can navigate by comparing the currently perceived view with memorised views along a familiar foraging route. Models regarding route-following suggest that the views are stored and recalled independently of the sequence in which they occur. Hence, the ant only needs to evaluate the instantaneous familiarity of the current view to obtain a heading direction. This study investigates whether ant homing behaviour is influenced by alterations in the sequence of views experienced along a familiar route, using the frequency of stop-and-scan behaviour as an indicator of the ant's navigational uncertainty. Ants were trained to forage between their nest and a feeder which they exited through a short channel before proceeding along the homeward route. In tests, ants were collected before entering the nest and released again in the channel, which was placed either in its original location or halfway along the route. Ants exiting the familiar channel in the middle of the route would thus experience familiar views in a novel sequence. Results show that ants exiting the channel scan significantly more when they find themselves in the middle of the route, compared with when emerging at the expected location near the feeder. This behaviour suggests that previously encountered views influence the recognition of current views, even when these views are highly familiar, revealing a sequence component to route memory. How information about view sequences could be implemented in the insect brain, as well as potential alternative explanations to our results, are discussed.

Finding a place and leaving a mark in memory formation

Preference for spatial locations to maximize favorable outcomes and minimize aversive experiences helps animals survive and adapt to the changing environment. Both visual and non-visual cues play a critical role in spatial navigation and memory of a place supports and guides these strategies. Here we present the neural, genetic and behavioral processes involved in place memory formation using Drosophila melanogaster with a focus on non-visual cue based spatial memories. The work presented here highlights the work done by Dr. Troy Zars and his colleagues with an emphasis on role of biogenic amines in learning, cell biological mechanisms of neural systems and behavioral plasticity of place conditioning.

The Central Complex as a Potential Substrate for Vector Based Navigation

Insects use path integration (PI) to maintain a home vector, but can also store and recall vector-memories that take them from home to a food location, and even allow them to take novel shortcuts between food locations. The neural circuit of the Central Complex (a brain area that receives compass and optic flow information) forms a plausible substrate for these behaviors. A recent model, grounded in neurophysiological and neuroanatomical data, can account for PI during outbound exploratory routes and the control of steering to return home. Here, we show that minor, hypothetical but neurally plausible, extensions of this model can additionally explain how insects could store and recall PI vectors to follow food-ward paths, take shortcuts, search at the feeder and re-calibrate their vector-memories with experience. In addition, a simple assumption about how one of multiple vector-memories might be chosen at any point in time can produce the development and maintenance of efficient routes between multiple locations, as observed in bees. The central complex circuitry is therefore well-suited to allow for a rich vector-based navigational repertoire.

How to Navigate in Different Environments and Situations: Lessons From Ants

Ants are a globally distributed insect family whose members have adapted to live in a wide range of different environments and ecological niches. Foraging ants everywhere face the recurring challenge of navigating to find food and to bring it back to the nest. More than a century of research has led to the identification of some key navigational strategies, such as compass navigation, path integration, and route following. Ants have been shown to rely on visual, olfactory, and idiothetic cues for navigational guidance. Here, we summarize recent behavioral work, focusing on how these cues are learned and stored as well as how different navigational cues are integrated, often between strategies and even across sensory modalities. Information can also be communicated between different navigational routines. In this way, a shared toolkit of fundamental navigational strategies can lead to substantial flexibility in behavioral outcomes. This allows individual ants to tune their behavioral repertoire to different tasks (e.g., foraging and homing), lifestyles (e.g., diurnal and nocturnal), or environments, depending on the availability and reliability of different guidance cues. We also review recent anatomical and physiological studies in ants and other insects that have started to reveal neural correlates for specific navigational strategies, and which may provide the beginnings of a truly mechanistic understanding of navigation behavior.

Path Integration: Combining Optic Flow with Compass Orientation

The discovery of translational optic flow detectors in the central complex of a bee has inspired a new model of path integration.