Bioinspired Approaches for Autonomous Small-Object Detection and Avoidance

Escobar-Alvarez, Hector D.; Ohradzansky, Michael; Keshavan, Jishnu; Ranganathan, Badri N.; Humbert, J. Sean

doi:10.1109/tro.2019.2922472

Cited by 22 publications

(15 citation statements)

References 55 publications

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“…The important features about obstacle detection, avoidance or mapping are addressed as follows [16]- [32]. In [16], a simple solution using the ultrasonic sensor for obstacle detection and collision avoidance of unmanned aerial vehicles optimized for and evaluated with quadrotor is demonstrated.…”

Section: Existing Workmentioning

confidence: 99%

“…In [31], the collision avoidance task is accomplished by exploiting convex inner approximations of the obstacle-free region and an ad hoc constraints switching procedure. In [32], two novel bioinspired approaches are proposed to extract information about small-field objects contained in planar optic flow.…”

Section: Existing Workmentioning

confidence: 99%

“…Only the simulations are presented in the studies [20], [24], [30]. The studies [19], [26], [29], [31], [32] are only for the indoor quadrotor. In [19], [26], [29], [31], [32], their online planning need a laptop and then transfer the processing result through the wireless module.…”

Section: Existing Workmentioning

confidence: 99%

“…Based on the analysis of (33) by (29)- (32) and the bounded estimation error of the EKF, the uncertainties can be relatively upper bounded by the following inequalities:…”

Section: Fuzzy Tracking Incremental Controlmentioning

confidence: 99%

“…A path generation method without the building of post-processed maps bypasses the costly map building and maintenance and achieves the best adaptation for different environments. There are many studies about (on-line) obstacle detection and avoidance for robot [16]- [32].…”

Section: Introductionmentioning

confidence: 99%

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On-Line Obstacle Detection, Avoidance, and Mapping of an Outdoor Quadrotor Using EKF-Based Fuzzy Tracking Incremental Control

Hwang

Lai

2019

IEEE Access

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The unknown two-dimensional obstacles, including different shapes, numbers, locations, and in the vicinity of the planning path for an outdoor quadrotor, are on-line detected by a 360-degree Li-Dar Sweep Scanse. Based on the comparison among detected triangles containing extreme points of each obstacle, the central orientation of the triangle with the maximum detected distance and the angle larger than the specific threshold is assigned to fly a specific distance for obstacle avoidance. Nevertheless, the quadrotor probably encounters a dead end and is then navigated to a specific altitude for the continuous procedure of obstacle detection. By on-line detection at different waypoints for the same obstacle, an obstacle mapping is also established by all the obstacle detections. Since the sensing signals of an outdoor quadrotor are easily affected by stochastic noise and the quadrotor is operated in ''x'' configuration, an extended Kalman filter based fuzzy tracking incremental control (EKF-FTIC) is employed to simultaneously execute the path tracking, obstacle avoidance, and target approach. Finally, the experiments with 5 unknown obstacles in the neighborhood of a planning path connecting start point with end point validate the effectiveness and feasibility of the proposed method. INDEX TERMS Extended Kalman filter, fuzzy tracking incremental control, on-line obstacle detection, avoidance and mapping, quadrotor.

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Section: Existing Workmentioning

confidence: 99%

Section: Existing Workmentioning

confidence: 99%

Section: Existing Workmentioning

confidence: 99%

“…Based on the analysis of (33) by (29)- (32) and the bounded estimation error of the EKF, the uncertainties can be relatively upper bounded by the following inequalities:…”

Section: Fuzzy Tracking Incremental Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

On-Line Obstacle Detection, Avoidance, and Mapping of an Outdoor Quadrotor Using EKF-Based Fuzzy Tracking Incremental Control

Hwang

Lai

2019

IEEE Access

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Modelling Drosophila motion vision pathways for decoding the direction of translating objects against cluttered moving backgrounds

Yue

2020

Biol Cybern

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Decoding the direction of translating objects in front of cluttered moving backgrounds, accurately and efficiently, is still a challenging problem. In nature, lightweight and low-powered flying insects apply motion vision to detect a moving target in highly variable environments during flight, which are excellent paradigms to learn motion perception strategies. This paper investigates the fruit fly Drosophila motion vision pathways and presents computational modelling based on cutting-edge physiological researches. The proposed visual system model features bio-plausible ON and OFF pathways, wide-field horizontal-sensitive (HS) and vertical-sensitive (VS) systems. The main contributions of this research are on two aspects: 1) the proposed model articulates the forming of both direction-selective (DS) and directionopponent (DO) responses, revealed as principal features of motion perception neural circuits, in a feed-forward manner; 2) it also shows robust direction selectivity to translating objects in front of cluttered moving backgrounds, via the modelling of spatiotemporal dynamics including combination of motion pre-filtering mechanisms and ensembles of local correlators inside both the ON and OFF pathways, which works effectively to suppress irrelevant background motion or distractors, and to improve the dynamic response. Accordingly, the direction of translating objects is de-This research has received funding from the European Unions Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 691154 STEP2DYNA and No 778602 ULTRACEPT.

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