Perching with a robotic insect using adaptive tracking control and iterative           learning control

Chirarattananon, Pakpong; Kevin, Y.; Wood, Robert J.

doi:10.1177/0278364916632896

Cited by 53 publications

(57 citation statements)

References 59 publications

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“…As a result, many demonstrations of pitch-up manoeuvres with physical prototypes, both with fixed wings and quadrotors, have relied on motion capture systems for absolute situational awareness. These systems have been used for experiments to empirically generate the required control for trajectory planning (figure 3a) [57,156] and can give continuous position feedback (figure 3c) [142,143,[157][158][159][160][161][162]. The few robots that have not required a motion capture system use sensors to detect a wall and initiate a pitch-up manoeuvre ( figure 3b,c) [18,51,52,163].…”

Section: Landing and Take-off In Aerial Robotsmentioning

confidence: 99%

Touchdown to take-off: at the interface of flight and surface locomotion

Roderick¹,

Cutkosky²,

Lentink³

2017

Interface Focus.

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Small aerial robots are limited to short mission times because aerodynamic and energy conversion efficiency diminish with scale. One way to extend mission times is to perch, as biological flyers do. Beyond perching, small robot flyers benefit from manoeuvring on surfaces for a diverse set of tasks, including exploration, inspection and collection of samples. These opportunities have prompted an interest in bimodal aerial and surface locomotion on both engineered and natural surfaces. To accomplish such novel robot behaviours, recent efforts have included advancing our understanding of the aerodynamics of surface approach and take-off, the contact dynamics of perching and attachment and making surface locomotion more efficient and robust. While current aerial robots show promise, flying animals, including insects, bats and birds, far surpass them in versatility, reliability and robustness. The maximal size of both perching animals and robots is limited by scaling laws for both adhesion and claw-based surface attachment. Biomechanists can use the current variety of specialized robots as inspiration for probing unknown aspects of bimodal animal locomotion. Similarly, the pitch-up landing manoeuvres and surface attachment techniques of animals can offer an evolutionary design guide for developing robots that perch on more diverse and complex surfaces.

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Section: Landing and Take-off In Aerial Robotsmentioning

confidence: 99%

Touchdown to take-off: at the interface of flight and surface locomotion

Roderick¹,

Cutkosky²,

Lentink³

2017

Interface Focus.

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“…Based on limited previous studies and experimental evidence, we proposed simple models to capture the effects of wind disturbances on the translational and rotational dynamics of the robot for control purposes. With a few simplifying assumptions, two disturbance rejection schemes compatible with the adaptive tracking flight controller previously developed in [17] were presented. The strategies were implemented and verified in a series of flight control experiments, including gusts with constant and time-varying wind speeds with air speed up to 80 cm s 21 (advance ratio J a ¼ 0.14).…”

Section: Conclusion and Discussionmentioning

confidence: 99%

“…In this paper, we present two wind disturbance rejection schemes and demonstrate how they can be implemented on the existing adaptive tracking flight controller presented in [17]. The controller is comprised of two primary components: an attitude controller and an altitude controller, operating in parallel.…”

Section: Flight Control Strategies 31 Adaptive Tracking Flight Contmentioning

confidence: 99%

Dynamics and flight control of a flapping-wing robotic insect in the presence of wind gusts

et al. 2017

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With the goal of operating a biologically inspired robot autonomously outside of laboratory conditions, in this paper, we simulated wind disturbances in a laboratory setting and investigated the effects of gusts on the flight dynamics of a millimetre-scale flapping-wing robot. Simplified models describing the disturbance effects on the robot's dynamics are proposed, together with two disturbance rejection schemes capable of estimating and compensating for the disturbances. The proposed methods are experimentally verified. The results show that these strategies reduced the root-mean-square position errors by more than 50% when the robot was subject to 80 cm s 21 horizontal wind. The analysis of flight data suggests that modulation of wing kinematics to stabilize the flight in the presence of wind gusts may indirectly contribute an additional stabilizing effect, reducing the time-averaged aerodynamic drag experienced by the robot. A benchtop experiment was performed to provide further support for this observed phenomenon.

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“…With the estimate of distance, aerial robots potentially benefit from the ability to deploy a landing gear at a suitable moment or to approach the surface at arbitrary speed [42,43]. That is, the landing task is no longer constrained to a constant rate of optic flow.…”

Section: Altitude Estimation During Landing Maneuversmentioning

confidence: 99%

A direct optic flow-based strategy for inverse flight altitude estimation with monocular vision and IMU measurements

Chirarattananon

2018

Bioinspir. Biomim.

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With tiny and limited nervous systems, insects demonstrate a remarkable ability to fly through complex environments. Optic flow has been identified to play a crucial role in regulating flight conditions and navigation in flies and bees. In robotics, optic flow has been widely studied thanks to the low computational requirements. However, with only monocular visual information, optic flow is inherently devoid of a scale factor required for estimating the absolute distance. In this paper, we propose a strategy for estimating the flight altitude of a flying robot with a ventral camera by combining the optic flow with measurements from an inertial measurement unit. Instead of using the prevalent feature-based approach for calculation of optic flow, we implement a direct method that evaluates the flow information via image gradients. We show that the direct approach notably simplifies the computation steps compared to the feature-based method. When combined with an extended Kalman filter for fusion of inertial measurement units measurements, the flight altitude can be estimated in real time. We carried out extensive flight tests in different settings. Among 31 hovering and vertical flights near the altitude of 40 cm, we achieved the RMS errors in the altitude estimate of 2.51 cm. Further analysis of factors that affect the quality of the flow and the distance estimate is also provided. PAPER Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence.

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Perching with a robotic insect using adaptive tracking control and iterative learning control

Cited by 53 publications

References 59 publications

Touchdown to take-off: at the interface of flight and surface locomotion

Touchdown to take-off: at the interface of flight and surface locomotion

Dynamics and flight control of a flapping-wing robotic insect in the presence of wind gusts

A direct optic flow-based strategy for inverse flight altitude estimation with monocular vision and IMU measurements

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