Jan Steckel

BatSLAM: Simultaneous localization and mapping using biomimetic sonar.

We propose to combine a biomimetic navigation model which solves a simultaneous localization and mapping task with a biomimetic sonar mounted on a mobile robot to address two related questions. First, can robotic sonar sensing lead to intelligent interactions with complex environments? Second, can we model sonar based spatial orientation and the construction of spatial maps by bats? To address these questions we adapt the mapping module of RatSLAM, a previously published navigation system based on computational models of the rodent hippocampus. We analyze the performance of the proposed robotic implementation operating in the real world. We conclude that the biomimetic navigation model operating on the information from the biomimetic sonar allows an autonomous agent to map unmodified (office) environments efficiently and consistently. Furthermore, these results also show that successful navigation does not require the readings of the biomimetic sonar to be interpreted in terms of individual objects/landmarks in the environment. We argue that the system has applications in robotics as well as in the field of biology as a simple, first order, model for sonar based spatial orientation and map building.

Broadband 3-D Sonar System Using a Sparse Array for Indoor Navigation

Array beamforming techniques allow for the generation of 3-D spatial filters which can be used to localize objects in a large field of view (FOV) without the need for mechanical scanning. By combining broadband beamforming with a sparse, random array of receivers, we have constructed a low-cost, yet powerful, in-air sonar system, which is suited for a wide range of robotic applications. Experimental results in unmodified office environments show the performance of the sonar sensor. In particular, we document the sensors capacity to produce 3-D location measurements in the presence of multiple highly overlapping echoes. We show how this capability makes possible the combination of a wide FOV with accurate 3-D localization, allowing the sensor to operate under real-time constraints in realistic environments. To demonstrate the use of this sensor, we describe an odometry application that estimates egomotion of a mobile robot using acoustic flow.

Information generated by the moving pinnae of Rhinolophus rouxi: tuning of the morphology at different harmonics.

Bats typically emit multi harmonic calls. Their head morphology shapes the emission and hearing sound fields as a function of frequency. Therefore, the sound fields are markedly different for the various harmonics. As the sound field provides bats with all necessary cues to locate objects in space, different harmonics might provide them with variable amounts of information about the location of objects. Also, the ability to locate objects in different parts of the frontal hemisphere might vary across harmonics. This paper evaluates this hypothesis in R. rouxi, using an information theoretic framework. We estimate the reflector position information transfer in the echolocation system of R. rouxi as a function of frequency. This analysis shows that localization performance reaches a global minimum and a global maximum at the two most energetic frequency components of R. rouxi call indicating tuning of morphology and harmonic structure. Using the fundamental the bat is able to locate objects in a large portion of the frontal hemisphere. In contrast, using the 1 overtone, it can only locate objects, albeit with a slightly higher accuracy, in a small portion of the frontal hemisphere by reducing sensitivity to echoes from outside this region of interest. Hence, different harmonic components provide the bat either with a wide view or a focused view of its environment. We propose these findings can be interpreted in the context of the foraging behaviour of R. rouxi, i.e., hunting in cluttered environments. Indeed, the focused view provided by the 1 overtone suggests that at this frequency its morphology is tuned for clutter rejection and accurate localization in a small region of interest while the finding that overall localization performance is best at the fundamental indicates that the morphology is simultaneously tuned to optimize overall localization performance at this frequency.

Place recognition using batlike sonar

Echolocating bats have excellent spatial memory and are able to navigate to salient locations using bio-sonar. Navigating and route-following require animals to recognize places. Currently, it is mostly unknown how bats recognize places using echolocation. In this paper, we propose template based place recognition might underlie sonar-based navigation in bats. Under this hypothesis, bats recognize places by remembering their echo signature - rather than their 3D layout. Using a large body of ensonification data collected in three different habitats, we test the viability of this hypothesis assessing two critical properties of the proposed echo signatures: (1) they can be uniquely classified and (2) they vary continuously across space. Based on the results presented, we conclude that the proposed echo signatures satisfy both criteria. We discuss how these two properties of the echo signatures can support navigation and building a cognitive map. DOI: http://dx.doi.org/10.7554/eLife.14188.001

Sonar System Combining an Emitter Array With a Sparse Receiver Array for Air-Coupled Applications

In this paper, we describe the application of an emitter array based on simultaneous transmit-synthetic aperture beamforming (ST-STAB) to improve the signal-to-noise ratio in an existing, 3-D, air-coupled sonar system. The ST-STAB approach allows for the simultaneous emission of orthogonal codes by an array of emitters, which are decoded in the receiver stage, eliminating the need for multiple measurement cycles. By adding more emitters to the sensor system, the overall emitted acoustic energy is increased, while the ST-STAB approach ensures an efficient use of measurement time. We elaborate on the mathematical model of the sensor and signal processing system, provide the associated point spread functions and show experimental validation the constructed prototype array.

A novel biomimetic sonarhead using beamforming technology to mimic bat echolocation

A novel biomimetic sonarhead has been developed to allow researchers of bat echolocation behavior and biomimetic sonar to perform experiments with a system similar to the bats sensory system. The bats echolocation-related transfer function (ERTF) is implemented using an array of receivers to implement the head-related transfer function (HRTF), and an array of emitters mounted on a cylindrical manifold to implement the emission pattern of the bat. The complete system is controlled by a field-programmable gate array (FPGA) based embedded system connected through a USB interface.

Biomimetic target localisation using an EMFi based array

Bats are known to use spectral cues to localise targets. We propose a similar localisation scheme making use of a sensor array built using EMFi material and a structured backplate. We present an adaptation of `delay and sum¿ beamforming that when combined with a broadband chirp results in accurate localisation (±2°) in a broad field of view [¿70°,70°].

Acoustic flow for robot motion control

In this paper we explore the use of 3D acoustic flow fields to steer robot motion. We derive the 3D velocity fields set up by linear and rotational robot motions and explain how they can be sampled directly by a sonar array-sensor that we developed recently. The resulting acoustic flow field patterns are then shown to contain all the information necessary for controlling obstacle avoidance and corridor following behavior. Experimental data collected by the sonar system mounted on a wheelchair that was driven in an office environment are presented to validate the theoretically predicted acoustic flow patterns.

Biomimetic sonar for biomimetic SLAM

We present a biomimetic sonar system consisting of a single emitter and two receivers endowed with realistic spatial filter characteristics by inserting them in plastic replicas of bat pinnae. The outputs of these receivers are processed by a simple functional model of the processing performed in the cochlea. We show that these cochleograms contain sufficient amounts of information for the robust localization of a robot in unmodified office environments. This localization component is part of a more general biomimetic Simultaneous Localization and Mapping system (SLAM) for an autonomous robot based on a model of the rodent Hippocampus and the use of sonar instead of vision as exteroceptive sensory input (BatSLAM). To quantify the performance of the biomimetic sonar system in the robot localization task, and to be able to quantitatively compare the performance of different types of (sonar) sensors, we propose a technique based on conditional entropy.

Spatial sampling strategy for a 3D sonar sensor supporting BatSLAM

In this paper, we present a solution to the Simultaneous Localization and Mapping problem by combining a novel 3D in-air sonar sensor with techniques for estimating the egomotion of a mobile platform (called acoustic flow odometry) and a bio-inspired mapping module (called BatSLAM). This combination eliminates the need for odometric information originating from the robots motor controller, enabling applications where that information is difficult to obtain, e.g. many electric wheelchairs. The proposed method exploits the programmable spatial sampling capabilities of the 3D sonar system to derive from the same set of received echo signals both an accurate representation of reflectors in the horizontal plane (2D energyscape) and a more coarse representation of reflectors in the frontal hemisphere (3D energyyscape). Using a mapping experiment we demonstrate that the motion estimates originating from the acoustic flow module combined with the coarse frontal hemisphere data provide sufficient information for the mapping module to reconstruct the robots trajectory.