This page has only limited features, please log in for full access.

Unclaimed
Mandyam V. Srinivasan
Queensland Brain Institute, University of Queensland, Brisbane, Australia

Basic Info

Basic Info is private.

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Conference paper
Published: 20 January 2021 in Proceedings of the Royal Society B: Biological Sciences
Reads 0
Downloads 0

To minimize the risk of colliding with the ground or other obstacles, flying animals need to control both their ground speed and ground height. This task is particularly challenging in wind, where head winds require an animal to increase its airspeed to maintain a constant ground speed and tail winds may generate negative airspeeds, rendering flight more difficult to control. In this study, we investigate how head and tail winds affect flight control in the honeybee Apis mellifera , which is known to rely on the pattern of visual motion generated across the eye—known as optic flow—to maintain constant ground speeds and heights. We find that, when provided with both longitudinal and transverse optic flow cues (in or perpendicular to the direction of flight, respectively), honeybees maintain a constant ground speed but fly lower in head winds and higher in tail winds, a response that is also observed when longitudinal optic flow cues are minimized. When the transverse component of optic flow is minimized, or when all optic flow cues are minimized, the effect of wind on ground height is abolished. We propose that the regular sidewards oscillations that the bees make as they fly may be used to extract information about the distance to the ground, independently of the longitudinal optic flow that they use for ground speed control. This computationally simple strategy could have potential uses in the development of lightweight and robust systems for guiding autonomous flying vehicles in natural environments.

ACS Style

Emily Baird; Norbert Boeddeker; Mandyam V. Srinivasan. The effect of optic flow cues on honeybee flight control in wind. Proceedings of the Royal Society B: Biological Sciences 2021, 288, 20203051 .

AMA Style

Emily Baird, Norbert Boeddeker, Mandyam V. Srinivasan. The effect of optic flow cues on honeybee flight control in wind. Proceedings of the Royal Society B: Biological Sciences. 2021; 288 (1943):20203051.

Chicago/Turabian Style

Emily Baird; Norbert Boeddeker; Mandyam V. Srinivasan. 2021. "The effect of optic flow cues on honeybee flight control in wind." Proceedings of the Royal Society B: Biological Sciences 288, no. 1943: 20203051.

Short communication
Published: 19 November 2020 in Biochemical and Biophysical Research Communications
Reads 0
Downloads 0

This review summarizes research carried out in the author’s laboratory investigating the ways in which honeybees use vision to guide their flight and navigate in their environment, and describes how these principles have been used to design, build and test biologically-inspired systems for the guidance and navigation of unmanned aerial vehicles. It also outlines studies investigating the capacities of honeybees in the areas of visual perception, pattern recognition, and ‘cognition’.

ACS Style

Mandyam V. Srinivasan. Vision, perception, navigation and ‘cognition’ in honeybees and applications to aerial robotics. Biochemical and Biophysical Research Communications 2020, 564, 4 -17.

AMA Style

Mandyam V. Srinivasan. Vision, perception, navigation and ‘cognition’ in honeybees and applications to aerial robotics. Biochemical and Biophysical Research Communications. 2020; 564 ():4-17.

Chicago/Turabian Style

Mandyam V. Srinivasan. 2020. "Vision, perception, navigation and ‘cognition’ in honeybees and applications to aerial robotics." Biochemical and Biophysical Research Communications 564, no. : 4-17.

Article
Published: 13 February 2020 in Scientific Reports
Reads 0
Downloads 0

We have investigated the paths taken by Budgerigars while flying in a tunnel. The flight trajectories of nine Budgerigars (Melopsittacus undulatus) were reconstructed in 3D from high speed stereo videography of their flights in an obstacle-free tunnel. Individual birds displayed highly idiosyncratic flight trajectories that were consistent from flight to flight over the course of several months. We then investigated the robustness of each bird’s trajectory by interposing a disk-shaped obstacle in its preferred flight path. We found that each bird continued to fly along its preferred trajectory up to a point very close to the obstacle before veering over the obstacle rapidly, making a minimal deviation to avoid a collision, and subsequently returning to its original path. Thus, Budgerigars show a high propensity to stick to their individual, preferred flight paths even when confronted with a clearly visible obstacle, and do not adopt a substantially different, unobstructed route. The robust preference for idiosyncratic flight paths, and the tendency to pass obstacles by flying above them, provide new insights into the strategies that underpin obstacle avoidance in birds. We believe that this is the first carefully controlled study of the behaviour of birds in response to a newly introduced obstacle in their flight path. The insights from the study could also have implications for conservation efforts to mitigate collisions of birds with man-made obstacles.

ACS Style

Debajyoti Karmaker; Julia Groening; Michael Wilson; Ingo Schiffner; Mandyam V. Srinivasan. Budgerigars adopt robust, but idiosyncratic flight paths. Scientific Reports 2020, 10, 1 -12.

AMA Style

Debajyoti Karmaker, Julia Groening, Michael Wilson, Ingo Schiffner, Mandyam V. Srinivasan. Budgerigars adopt robust, but idiosyncratic flight paths. Scientific Reports. 2020; 10 (1):1-12.

Chicago/Turabian Style

Debajyoti Karmaker; Julia Groening; Michael Wilson; Ingo Schiffner; Mandyam V. Srinivasan. 2020. "Budgerigars adopt robust, but idiosyncratic flight paths." Scientific Reports 10, no. 1: 1-12.

Original paper
Published: 03 February 2020 in Journal of Comparative Physiology A
Reads 0
Downloads 0

This study examines the visual acuity of Queensland fruit flies (Bactrocera tryoni) by analysing their turning responses to an immersive visual stimulus consisting of a pattern of vertical stripes presented at various angular periods and rotational rates. The results infer that these flies possess an interommatidial angle of approximately \({2}^{\circ }\), and an ommatidial acceptance angle of approximately \({1.72}^{\circ }\). This suggests that the visual acuity of Queensland fruit flies is substantially better than that of the classical vinegar fly (Drosophila melanogaster), and is comparable to those of the housefly (Musca domestica) and the honeybee (Apis mellifera). The contrast sensitivity of Queensland fruit flies is comparable to that of the housefly.

ACS Style

Kiaran K. K. Lawson; Mandyam V. Srinivasan. Contrast sensitivity and visual acuity of Queensland fruit flies (Bactrocera tryoni). Journal of Comparative Physiology A 2020, 206, 419 -428.

AMA Style

Kiaran K. K. Lawson, Mandyam V. Srinivasan. Contrast sensitivity and visual acuity of Queensland fruit flies (Bactrocera tryoni). Journal of Comparative Physiology A. 2020; 206 (3):419-428.

Chicago/Turabian Style

Kiaran K. K. Lawson; Mandyam V. Srinivasan. 2020. "Contrast sensitivity and visual acuity of Queensland fruit flies (Bactrocera tryoni)." Journal of Comparative Physiology A 206, no. 3: 419-428.

Author correction
Published: 24 May 2019 in Scientific Reports
Reads 0
Downloads 0

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

ACS Style

Mandiyam Y. Mahadeeswara; Mandyam V. Srinivasan. Author Correction: Coordinated Turning Behaviour of Loitering Honeybees. Scientific Reports 2019, 9, 8054 .

AMA Style

Mandiyam Y. Mahadeeswara, Mandyam V. Srinivasan. Author Correction: Coordinated Turning Behaviour of Loitering Honeybees. Scientific Reports. 2019; 9 (1):8054.

Chicago/Turabian Style

Mandiyam Y. Mahadeeswara; Mandyam V. Srinivasan. 2019. "Author Correction: Coordinated Turning Behaviour of Loitering Honeybees." Scientific Reports 9, no. 1: 8054.

Preprint
Published: 05 April 2019
Reads 0
Downloads 0

We have investigated the paths taken by Budgerigars while flying in a tunnel. The preferred flight trajectories of nine Budgerigars (Melopsittacus undulatus) were reconstructed in 3D from high speed stereo videography of their flights in an obstacle-free tunnel. Individual birds displayed highly idiosyncratic flight trajectories that were consistent from flight to flight over the course of several months. We then investigated the robustness of each bird’s trajectory by interposing a disk-shaped obstacle in its preferred flight path. We found that each bird continued to fly along its preferred trajectory up to a point very close to the obstacle before veering away rapidly, making a minimal deviation to avoid a collision, and subsequently returning to its original path. Thus, Budgerigars show a high propensity to stick to their individual, preferred flight paths even when confronted with a clearly visible obstacle, and do not adopt a substantially different, safer route. Detailed analysis of the last-minute avoidance manoeuvre suggests that a collision is avoided by restricting the magnitude of the optic flow generated by the obstacle to a maximum value of about 700 deg/sec. The robust preference for idiosyncratic flight paths, and the tendency to pass obstacles by flying above them, provide new insights into the strategies that underpin obstacle avoidance in birds. It could also have wide-ranging implications for conservation efforts to mitigate collisions of birds with man-made obstacles – especially obstacles that are poorly visible, such as wind turbines or buildings with glass facades. Our findings indicate that care needs to be exercised to ensure that newly planned structures are not located near major bird flyways, wherever possible, and to ensure that the positioning takes into consideration the cues and behaviours that birds use to avoid such obstacles.

ACS Style

Debajyoti Karmaker; Ingo Schiffner; Mandyam V. Srinivasan. Budgerigars adopt robust, but idiosyncratic flight paths. 2019, 598680 .

AMA Style

Debajyoti Karmaker, Ingo Schiffner, Mandyam V. Srinivasan. Budgerigars adopt robust, but idiosyncratic flight paths. . 2019; ():598680.

Chicago/Turabian Style

Debajyoti Karmaker; Ingo Schiffner; Mandyam V. Srinivasan. 2019. "Budgerigars adopt robust, but idiosyncratic flight paths." , no. : 598680.

Journal article
Published: 16 November 2018 in Scientific Reports
Reads 0
Downloads 0

Turning during flight is a complex behaviour that requires coordination to ensure that the resulting centrifugal force is never large enough to disrupt the intended turning trajectory. The centrifugal force during a turn increases with the curvature (sharpness) of the turn, as well as the speed of flight. Consequently, sharp turns would require lower flight speeds, in order to limit the centrifugal force to a manageable level and prevent unwanted sideslips. We have video-filmed honeybees flying near a hive entrance when the entrance is temporarily blocked. A 3D reconstruction and analysis of the flight trajectories executed during this loitering behaviour reveals that sharper turns are indeed executed at lower speeds. During a turn, the flight speed is matched to the curvature, moment to moment, in such a way as to maintain the centrifugal force at an approximately constant, low level of about 30% of the body weight, irrespective of the instantaneous speed or curvature of the turn. This ensures that turns are well coordinated, with few or no sideslips - as it is evident from analysis of other properties of the flight trajectories.

ACS Style

Mandiyam Y. Mahadeeswara; Mandyam V. Srinivasan. Coordinated Turning Behaviour of Loitering Honeybees. Scientific Reports 2018, 8, 16942 .

AMA Style

Mandiyam Y. Mahadeeswara, Mandyam V. Srinivasan. Coordinated Turning Behaviour of Loitering Honeybees. Scientific Reports. 2018; 8 (1):16942.

Chicago/Turabian Style

Mandiyam Y. Mahadeeswara; Mandyam V. Srinivasan. 2018. "Coordinated Turning Behaviour of Loitering Honeybees." Scientific Reports 8, no. 1: 16942.

Conference paper
Published: 10 November 2018 in Transactions on Petri Nets and Other Models of Concurrency XV
Reads 0
Downloads 0

Object detection and tracking are active and important research areas in computer vision as well as neuroscience. Of particular interest is the detection and tracking of small, poorly lit, deformable objects in the presence of sensor noise, and large changes in background and foreground illumination. Such conditions are frequently encountered when an animal moves in its natural environment, or in an experimental arena. The problems are exacerbated with the use of high-speed video cameras as the exposure time for high-speed cameras is limited by the frame rate, which limits the SNR. In this paper we present a set of simple algorithms for detecting and tracking multiple, small, poorly lit, deformable objects in environments that feature drastic changes in background and foreground illumination, and poor signal-to-noise ratios. These novel algorithms are shown to exhibit better performance than currently available state-of-the art algorithms.

ACS Style

Debajyoti Karmaker; Ingo Schiffner; Michael Wilson; Mandyam V. Srinivasan. The Bird Gets Caught by the WORM: Tracking Multiple Deformable Objects in Noisy Environments Using Weight ORdered Logic Maps. Transactions on Petri Nets and Other Models of Concurrency XV 2018, 332 -343.

AMA Style

Debajyoti Karmaker, Ingo Schiffner, Michael Wilson, Mandyam V. Srinivasan. The Bird Gets Caught by the WORM: Tracking Multiple Deformable Objects in Noisy Environments Using Weight ORdered Logic Maps. Transactions on Petri Nets and Other Models of Concurrency XV. 2018; ():332-343.

Chicago/Turabian Style

Debajyoti Karmaker; Ingo Schiffner; Michael Wilson; Mandyam V. Srinivasan. 2018. "The Bird Gets Caught by the WORM: Tracking Multiple Deformable Objects in Noisy Environments Using Weight ORdered Logic Maps." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 332-343.

Journal article
Published: 08 October 2018 in IFAC-PapersOnLine
Reads 0
Downloads 0

In this paper, we investigate an inverse differential game approach to modelling the mid-air collision avoidance behaviours of birds. We propose a general method for estimating the cost-functional parameters of a noncooperative differential game from partial-state measurements of an open-loop Nash equilibrium. We apply the method to data of birds performing mid-air collision avoidance. Our analysis suggests that a differential game model provides a close description of the observed bird behaviours, and could provide new insights for the design of collision avoidance strategies for unmanned aircraft.

ACS Style

Timothy L. Molloy; Grace S. Garden; Tristan Perez; Ingo Schiffner; Debajyoti Karmaker; Mandyam V. Srinivasan. An Inverse Differential Game Approach to Modelling Bird Mid-Air Collision Avoidance Behaviours. IFAC-PapersOnLine 2018, 51, 754 -759.

AMA Style

Timothy L. Molloy, Grace S. Garden, Tristan Perez, Ingo Schiffner, Debajyoti Karmaker, Mandyam V. Srinivasan. An Inverse Differential Game Approach to Modelling Bird Mid-Air Collision Avoidance Behaviours. IFAC-PapersOnLine. 2018; 51 (15):754-759.

Chicago/Turabian Style

Timothy L. Molloy; Grace S. Garden; Tristan Perez; Ingo Schiffner; Debajyoti Karmaker; Mandyam V. Srinivasan. 2018. "An Inverse Differential Game Approach to Modelling Bird Mid-Air Collision Avoidance Behaviours." IFAC-PapersOnLine 51, no. 15: 754-759.

Published erratum
Published: 01 August 2018 in Journal of Experimental Biology
Reads 0
Downloads 0

In Materials and Methods, ‘Virtual reality flight platform’, the units for pitch torque were incorrect. The corrected sentence is given below.

ACS Style

Kiaran K. K. Lawson; Mandyam V. Srinivasan. Correction: Flight control of fruit flies: dynamic response to optic flow and headwind (doi:10.1242/jeb.153056). Journal of Experimental Biology 2018, 221, jeb189720 .

AMA Style

Kiaran K. K. Lawson, Mandyam V. Srinivasan. Correction: Flight control of fruit flies: dynamic response to optic flow and headwind (doi:10.1242/jeb.153056). Journal of Experimental Biology. 2018; 221 (15):jeb189720.

Chicago/Turabian Style

Kiaran K. K. Lawson; Mandyam V. Srinivasan. 2018. "Correction: Flight control of fruit flies: dynamic response to optic flow and headwind (doi:10.1242/jeb.153056)." Journal of Experimental Biology 221, no. 15: jeb189720.

Journal article
Published: 25 July 2018 in Robotica
Reads 0
Downloads 0

SUMMARYA novel pure-vision egomotion estimation algorithm is presented, with extensions to Unmanned Aerial Systems (UAS) navigation through visual odometry. Our proposed method computes egomotion in two stages using panoramic images segmented into sky and ground regions. Rotations (in 3DOF) are estimated by using a customised algorithm to measure the motion of the sky image, which is affected only by the rotation of the aircraft, and not by its translation. The rotation estimate is then used to derotate the optic flow field generated by the ground, from which the translation of the aircraft (in 3DOF) is estimated by another customised, iterative algorithm. Segmentation of the rotation and translation estimations allows for a partial relaxation of the planar ground assumption, inherently increasing the robustness of the approach. The translation vectors are scaled using stereo-based height to compute the current UAS position through path integration for closed-loop navigation. Outdoor field tests of our approach in a small quadrotor UAS suggest that the technique is comparable to the performance of existing state-of-the-art vision-based navigation algorithms, whilst also removing all dependence on additional sensors, such as an IMU or global positioning system (GPS).

ACS Style

Tasarinan Jouir; Reuben Strydom; Thomas M. Stace; Mandyam V. Srinivasan. Vision-only egomotion estimation in 6DOF using a sky compass. Robotica 2018, 36, 1571 -1589.

AMA Style

Tasarinan Jouir, Reuben Strydom, Thomas M. Stace, Mandyam V. Srinivasan. Vision-only egomotion estimation in 6DOF using a sky compass. Robotica. 2018; 36 (10):1571-1589.

Chicago/Turabian Style

Tasarinan Jouir; Reuben Strydom; Thomas M. Stace; Mandyam V. Srinivasan. 2018. "Vision-only egomotion estimation in 6DOF using a sky compass." Robotica 36, no. 10: 1571-1589.

Other
Published: 06 June 2018
Reads 0
Downloads 0

Video cameras are finding increasing use in the study and analysis of bird flight over short ranges. However, reconstruction of flight trajectories in three dimensions typically requires the use of multiple cameras and elaborate calibration procedures. We present an alternative approach that uses a single video camera and a simple calibration procedure for the reconstruction of such trajectories. The technique combines prior knowledge of the wingspan of the bird with a camera calibration procedure that needs to be used only once in the lifetime of the system. The system delivers the exact 3D coordinates of the bird, and its roll angle, at the time of every full wing extension and uses interpolated height estimates to compute the 3D positions of the bird in the video frames between successive wing extensions. The system is inexpensive, compact and portable, and can be easily deployed in the laboratory as well as the field.

ACS Style

Mandyam V Srinivasan; Hong D Vo; Ingo Schiffner. 3D Reconstruction of Bird Flight Using a Single Video Camera. 2018, 340232 .

AMA Style

Mandyam V Srinivasan, Hong D Vo, Ingo Schiffner. 3D Reconstruction of Bird Flight Using a Single Video Camera. . 2018; ():340232.

Chicago/Turabian Style

Mandyam V Srinivasan; Hong D Vo; Ingo Schiffner. 2018. "3D Reconstruction of Bird Flight Using a Single Video Camera." , no. : 340232.

Preprint
Published: 03 June 2018
Reads 0
Downloads 0

Turning during flight is a complex behaviour that requires coordination to ensure that the resulting centrifugal force is never large enough to disrupt the intended turning trajectory. The centrifugal force during a turn increases with the curvature (sharpness) of the turn, as well as the speed of flight. Consequently, sharp turns would require lower flight speeds, in order to limit the centrifugal force to a manageable level and prevent unwanted sideslips. We have video-filmed honeybees flying near a hive entrance when the entrance is temporarily blocked. A 3D reconstruction and analysis of the flight trajectories executed during this loitering behaviour reveals that sharper turns are indeed executed at lower speeds. During a turn, the flight speed is matched to the curvature, moment to moment, in such a way as to maintain the centrifugal force at an approximately constant, low level of about 30% of the body weight, irrespective of the speed or the curvature of the turn. This ensures that turns are well coordinated, with few or no sideslips - as is evident from analysis of other properties of the flight trajectories.

ACS Style

Mandiyam Y. Mahadeeswara; Mandyam V. Srinivasan. Coordinated Turning Behaviour of Loitering Honeybees (Apis Mellifera). 2018, 332379 .

AMA Style

Mandiyam Y. Mahadeeswara, Mandyam V. Srinivasan. Coordinated Turning Behaviour of Loitering Honeybees (Apis Mellifera). . 2018; ():332379.

Chicago/Turabian Style

Mandiyam Y. Mahadeeswara; Mandyam V. Srinivasan. 2018. "Coordinated Turning Behaviour of Loitering Honeybees (Apis Mellifera)." , no. : 332379.

Conference paper
Published: 01 June 2018 in 2018 International Conference on Unmanned Aircraft Systems (ICUAS)
Reads 0
Downloads 0

Proportional, Integral and Derivative (PID) controllers are among the most commonly used control systems throughout industry, and there is an increasing need to tune such controllers effectively and rapidly, especially in varying dynamic conditions. Here we present two versions of a generalized, iterative method for tuning PID controllers: Iterative Root Mean Square Optimization (iRMSE) and Iterative Weighted Root Mean Square Optimization (iWRMSE). The two methods are validated in Matlab and in a virtual environment, as well as in field tests with a quadcopter. The performance of our two methods are compared against five popular methods: Zeigler-Nichols, Cohen-Coon, Lambda, Root Mean Square Error (RMSE) and Integral Square Error (ISE). We find that iWRMSE optimization delivers performance that is better than that obtained using all of the other methods, including manual tuning. Both iRMSE and iWRMSE can be used on a wide range of systems. Due to their iterative nature, they are also likely to be more suitable for systems operating in noisy or variable environments.

ACS Style

Holly J. Wright; Reuben Strydom; Mandyam V. Srinivasan. A generalized algorithm for tuning UAS flight controllers*. 2018 International Conference on Unmanned Aircraft Systems (ICUAS) 2018, 1369 -1378.

AMA Style

Holly J. Wright, Reuben Strydom, Mandyam V. Srinivasan. A generalized algorithm for tuning UAS flight controllers*. 2018 International Conference on Unmanned Aircraft Systems (ICUAS). 2018; ():1369-1378.

Chicago/Turabian Style

Holly J. Wright; Reuben Strydom; Mandyam V. Srinivasan. 2018. "A generalized algorithm for tuning UAS flight controllers*." 2018 International Conference on Unmanned Aircraft Systems (ICUAS) , no. : 1369-1378.

Review article
Published: 16 March 2018 in Frontiers in Neuroscience
Reads 0
Downloads 0

Over the last half century, work with flies, bees, and moths have revealed a number of visual guidance strategies for controlling different aspects of flight. Some algorithms, such as the use of pattern velocity in forward flight, are employed by all insects studied so far, and are used to control multiple flight tasks such as regulation of speed, measurement of distance, and positioning through narrow passages. Although much attention has been devoted to long-range navigation and homing in birds, until recently, very little was known about how birds control flight in a moment-to-moment fashion. A bird that flies rapidly through dense foliage to land on a branch—as birds often do—engages in a veritable three-dimensional slalom, in which it has to continually dodge branches and leaves, and find, and possibly even plan a collision-free path to the goal in real time. Each mode of flight from take-off to goal could potentially involve a different visual guidance algorithm. Here, we briefly review strategies for visual guidance of flight in insects, synthesize recent work from short-range visual guidance in birds, and offer a general comparison between the two groups of organisms.

ACS Style

Douglas L. Altshuler; Mandyam V. Srinivasan. Comparison of Visually Guided Flight in Insects and Birds. Frontiers in Neuroscience 2018, 12, 157 .

AMA Style

Douglas L. Altshuler, Mandyam V. Srinivasan. Comparison of Visually Guided Flight in Insects and Birds. Frontiers in Neuroscience. 2018; 12 ():157.

Chicago/Turabian Style

Douglas L. Altshuler; Mandyam V. Srinivasan. 2018. "Comparison of Visually Guided Flight in Insects and Birds." Frontiers in Neuroscience 12, no. : 157.

Research article
Published: 02 November 2017 in PLOS ONE
Reads 0
Downloads 0

Flying insects constantly face the challenge of choosing efficient, safe and collision-free routes while navigating through dense foliage. We examined the route-choice behavior of foraging honeybees when they encountered a barrier which could be traversed by flying through one of two apertures, positioned side by side. When the bees’ choice behavior was averaged over the entire tested population, the two apertures were chosen with equal frequency when they were equally wide. When the apertures were of different width, the bees, on average, showed a preference for the wider aperture, which increased sharply with the difference between the aperture widths. Thus, bees are able to discriminate the widths of oncoming gaps and choose the passage which is presumably safer and quicker to transit. Examination of the behavior of individual bees revealed that, when the two apertures were equally wide, ca. 55% of the bees displayed no side bias in their choices. However, the remaining 45% showed varying degrees of bias, with one half of them preferring the left-hand aperture, and the other half the right-hand aperture. The existence of distinct individual biases was confirmed by measuring the times required by biased bees to transit various aperture configurations: The transit time was longer if a bee’s intrinsic bias forced it to engage with the narrower aperture. Our results show that, at the population level, bees do not exhibit ‘handedness’ in choosing routes; however, individual bees display an idiosyncratic bias that can range from a strong left bias, through zero bias, to a strong right bias. In honeybees, previous studies of olfactory and visual learning have demonstrated clear biases at the population level. To our knowledge, our study is the first to uncover the existence of individually distinct biases in honeybees. We also show how a distribution of biases among individual honeybees can be advantageous in facilitating rapid transit of a group of bees through a cluttered environment, without any centralized decision-making or control.

ACS Style

Marielle Ong; Michael Bulmer; Julia Groening; Mandyam V. Srinivasan. Obstacle traversal and route choice in flying honeybees: Evidence for individual handedness. PLOS ONE 2017, 12, e0184343 .

AMA Style

Marielle Ong, Michael Bulmer, Julia Groening, Mandyam V. Srinivasan. Obstacle traversal and route choice in flying honeybees: Evidence for individual handedness. PLOS ONE. 2017; 12 (11):e0184343.

Chicago/Turabian Style

Marielle Ong; Michael Bulmer; Julia Groening; Mandyam V. Srinivasan. 2017. "Obstacle traversal and route choice in flying honeybees: Evidence for individual handedness." PLOS ONE 12, no. 11: e0184343.

Book chapter
Published: 11 September 2017 in Encyclopedia of Animal Cognition and Behavior
Reads 0
Downloads 0

IntroductionWhen an animal moves, the image of its surrounding environment moves in the retinae of the animal’s eyes. The pattern of image motion (known as the “optic flow field,” OFF) bears rich information about the animal’s own motion (termed “egomotion”), about the distance to various nearby objects, the speed of locomotion, the distance the animal has traveled, and several other parameters. This entry highlights some of the cues that are contained in the optic flow field and describes how they are used to control locomotion and enable safe and accurate navigation through the environment.The Relation of Optic Flow to EgomotionWhen a flying animal turns (yaws) to the left, the image of the world appears to move to the right and vice versa. The OFF generated by a leftward yaw (counterclockwise rotation about the dorso-ventral axis) is shown in Fig. 1a, where the individual vectors depict the direction and magnitude of the image motion at each location in the animal’s visual field (wh ...

ACS Style

Mandyam V. Srinivasan. Optic Flow. Encyclopedia of Animal Cognition and Behavior 2017, 1 -5.

AMA Style

Mandyam V. Srinivasan. Optic Flow. Encyclopedia of Animal Cognition and Behavior. 2017; ():1-5.

Chicago/Turabian Style

Mandyam V. Srinivasan. 2017. "Optic Flow." Encyclopedia of Animal Cognition and Behavior , no. : 1-5.

Comment
Published: 01 May 2017 in Learning & Behavior
Reads 0
Downloads 0

Animal navigation has fascinated biologists and engineers for centuries, and some of the most illuminating discoveries have come from the study of creatures with a brain no larger than a sesame seed. In an elegant recent study, Pfeiffer and Wittlinger (Science, 353, 1155–1157, 2016) have shown the means by which desert ants, carried from one nest to another by a relative, find their own way back home if they are accidentally dropped en route.

ACS Style

Mandyam V. Srinivasan. How lost “passenger” ants find their way home. Learning & Behavior 2017, 46, 1 -2.

AMA Style

Mandyam V. Srinivasan. How lost “passenger” ants find their way home. Learning & Behavior. 2017; 46 (1):1-2.

Chicago/Turabian Style

Mandyam V. Srinivasan. 2017. "How lost “passenger” ants find their way home." Learning & Behavior 46, no. 1: 1-2.

Journal article
Published: 01 January 2017 in Journal of Experimental Biology
Reads 0
Downloads 0

Insects are magnificent fliers that are capable of performing many complex tasks such as speed regulation, smooth landings, and collision avoidance, even though their computational abilities are limited by their small brain. To investigate how flying insects respond to changes in wind speed and surrounding optic flow, the open-loop sensorimotor response of female Queensland fruit flies (Bactrocera tryoni) was examined. 136 flies were exposed to stimuli comprising sinusoidally varying optic flow and air flow (simulating forward movement) under tethered conditions in a virtual reality arena. Two responses were measured: the thrust, and the abdomen pitch. The dynamics of the responses to optic flow and air flow were measured at various frequencies, and modelled as a multicompartment linear system, which accurately captures the fruit flies' behavioural responses. The results indicate that these two behavioural responses are concurrently sensitive to changes of optic flow as well as wind. The abdomen pitch showed a streamlining response, where the abdomen was raised higher as the magnitude of either stimulus was increased. The thrust, on the other hand, exhibited a counter-phase response where maximum thrust occurred when the optic flow or wind flow was at a minimum, indicating that the flies were attempting to maintain an ideal flight speed. When the changes in the wind and optic flow were in phase (i.e. did not contradict each other), the net responses (thrust and abdomen pitch) were well approximated by an equally weighted sum of the responses to the individual stimuli. However, when the optic flow and wind stimuli were presented in counterphase, the flies seemed to respond to only one stimulus or the other, demonstrating a form of ‘selective attention’.

ACS Style

Kiaran K. K. Lawson; Mandyam V. Srinivasan. Flight control of fruit flies: dynamic response to optic-flow and headwind. Journal of Experimental Biology 2017, 220, 2005 -2016.

AMA Style

Kiaran K. K. Lawson, Mandyam V. Srinivasan. Flight control of fruit flies: dynamic response to optic-flow and headwind. Journal of Experimental Biology. 2017; 220 (11):2005-2016.

Chicago/Turabian Style

Kiaran K. K. Lawson; Mandyam V. Srinivasan. 2017. "Flight control of fruit flies: dynamic response to optic-flow and headwind." Journal of Experimental Biology 220, no. 11: 2005-2016.

Conference paper
Published: 01 November 2016 in 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV)
Reads 0
Downloads 0

We describe a technique for object detection that uses a combination of global shape descriptors and local point descriptors. Our system is able to represent pose using a global shape descriptor, rather than the commonly used part based representation. This approach considerably reduces computational complexity and achieves a significant performance improvement on an extensive dataset: CUB-200-2011 [31]. Our methodology is valuable for the detection of textured objects that are viewed against background clutter and possess a high degree of articulation and variation of pose, as for example in birds. We demonstrate how high and low frequency gradients can be separated to better deal with the presence of interfering textures or stripes within the body, which is a major problem in the detection of bird-like objects. Furthermore, detection accuracy is improved by integrating appropriately designed scale invariant color features into the algorithm.

ACS Style

Debajyoti Karmaker; Ingo Schiffner; Reuben Strydom; Mandyam V. Srinivasan. WHoG: A weighted HoG-based scheme for the detection of birds and identification of their poses in natural environments. 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV) 2016, 1 -7.

AMA Style

Debajyoti Karmaker, Ingo Schiffner, Reuben Strydom, Mandyam V. Srinivasan. WHoG: A weighted HoG-based scheme for the detection of birds and identification of their poses in natural environments. 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV). 2016; ():1-7.

Chicago/Turabian Style

Debajyoti Karmaker; Ingo Schiffner; Reuben Strydom; Mandyam V. Srinivasan. 2016. "WHoG: A weighted HoG-based scheme for the detection of birds and identification of their poses in natural environments." 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV) , no. : 1-7.