Neuroscience of vision and aerial robotics

Research from Srinivasan’s laboratory has transformed our understanding of the elegant ‘short cuts’ that are used by animals with small brains and relatively simple nervous systems to see and perceive their world, and to navigate in it. Their studies have revealed how flying insects negotiate narrow gaps, regulate the height and speed of flight, estimate distance flown, and orchestrate smooth landings. Apart from enhancing fundamental knowledge, these findings are leading to novel, biologically inspired approaches to the design of guidance systems for unmanned aerial vehicles with applications in the areas of surveillance, security and planetary exploration.

Currently the group is working on four projects in the area of mid-air collision avoidance:

  1. Collision avoidance in ‘bee clouds’. The flights of a  number honeybees moving in a high-density air space are being video-filmed and analysed to understand the strategies that insects use to predict and avert imminent collisions.
  2. Collision avoidance in bird flight. High-speed video footage of budgerigars flying past each other in a special purpose bird flight tunnel, or avoiding other stationary or moving obstacles,  is being analysed to understand the strategies that birds use to predict and avert imminent collisions.
  3. Collision avoidance in virtual reality. Collsion avoidance is being investigated in Queensland fruitflies, tethered in a virtual-reality area to simulate flight through a dense forest.
  4. Biologically-inspired mid-air collision avoidance strategies for aircraft.The biological strategies uncovered in projects (i), (ii) and (iii), are being used in combination  with mathematical algorithms to design novel aircraft guidance strategies for sensing and avoiding imminent collisions. These strategies are being implemented and tested in multi-rotor aircraft equipped with biologically-inspired vision systems.

Contact

  +61 7 334 66322

  m.srinivasan@uq.edu.au

  Lab website


Group Publications

Research Areas

  • Collision avoidance in ‘bee clouds’
  • Collision avoidance in bird flight
  • Collision avoidance in virtual reality
  • Biologically-inspired mid-air collision avoidance strategies for aircraft


Apply for a PhD

Group Leader

  • Professor Srini Srinivasan

    Professor
    School of Information Technology and Electrical Engineering
    Professorial Research Fellow
    Queensland Brain Institute

Students


Support Staff

  • Mr Peter Ryan

    Telephony Technology Officer
    Information Technology Services
    Casual Research Assistant
    Queensland Brain Institute

How lost "passenger" ants find their way home
Srinivasan, Mandyam V. (2017) How lost "passenger" ants find their way home. Learning and Behavior, 1-2. doi:10.3758/s13420-017-0275-0

Optic flow
M.V. Srinivasan (2017) Optic flow. In: J. Vonk, T.K. Shackelford (eds.), Encyclopedia of Animal Cognition and Behavior. https://doi.org/10.1007/978-3-319-47829-6_1299-1, Springer International Publishing AG.

Comparison of visually guided flight in insects and birds
Altshuler, Douglas L. and Srinivasan, Mandyam V. (2018) Comparison of visually guided flight in insects and birds. Frontiers in Neuroscience12 157. doi:10.3389/fnins.2018.00157

TCM: a vision-based algorithm for distinguishing between stationary and moving objects irrespective of depth contrast from a UAS
Strydom, Reuben, Thurrowgood, Saul, Denuelle, Aymeric and Srinivasan, Mandyam V. (2016) TCM: a vision-based algorithm for distinguishing between stationary and moving objects irrespective of depth contrast from a UAS. International Journal of Advanced Robotic Systems13 3: . doi:10.5772/62846

A sparse snapshot-based navigation strategy for UAS guidance in natural environments
Denuelle, Aymeric and Srinivasan, Mandyam V. (2016). A sparse snapshot-based navigation strategy for UAS guidance in natural environments. In: 2016 IEEE International Conference on Robotics and Automation (ICRA). IEEE International Conference on Robotics and Automation, Stockholm, Sweden, (3455-3462). 16-21 May 2016. doi:10.1109/ICRA.2016.7487524

Anticipatory manoeuvres in bird flight
Vo, Hong D., Schiffner, Ingo and Srinivasan, Mandyam V. (2016) Anticipatory manoeuvres in bird flight. Scientific Reports6 27591: 1-8. doi:10.1038/srep27591

Budgerigar flight in a varying environment: flight at distinct speeds?
Schiffner, Ingo and Srinivasan, Mandyam V. (2016) Budgerigar flight in a varying environment: flight at distinct speeds?. Biology Letters12 6: 1-4. doi:10.1098/rsbl.2016.0221

WHoG: a weighted HOG-based scheme for the detection of birds and identification of their poses in natural environments
Karmaker, Debajyoti, Schiffner, Ingo, Strydom, Reuben and Srinivasan, Mandyam V (2017). WHoG: a weighted HOG-based scheme for the detection of birds and identification of their poses in natural environments. In: 2016 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016. 14th International Conference on Control, Automation, Robotics and Vision, ICARCV 2016, Phuket, Thailand, (). 13 - 15 November 2016. doi:10.1109/ICARCV.2016.7838650

A mid-air collision warning system: vision-based estimation of collision threats for aircraft
Gunasinghe, Dasun, Strydom, Reuben and Srinivasan, Mandyam V. (2016). A mid-air collision warning system: vision-based estimation of collision threats for aircraft. In: ACRA 2016: Australasian Conference on Robotics and Automation. Australasian Conference on Robotics and Automation, Brisbane, QLD, Australia, (). 5-7 December 2016.

Strategies for pre-emptive mid-air collision avoidance in budgerigars
Schiffner, Ingo, Perez, Tristan and Srinivasan, Mandyam V. (2016) Strategies for pre-emptive mid-air collision avoidance in budgerigars. PLoS One11 9: . doi:10.1371/journal.pone.0162435

In search of evidence for the experience of pain in honeybees: a self-administration study
Groening, Julia, Venini, Dustin and Srinivasan, Mandyam V. (2017) In search of evidence for the experience of pain in honeybees: a self-administration study. Scientific Reports7 . doi:10.1038/srep45825

Obstacle traversal and route choice in flying honeybees: Evidence for individual handedness
Ong, Marielle, Bulmer, Michael, Groening, Julia and Srinivasan, Mandyam V (2017) Obstacle traversal and route choice in flying honeybees: Evidence for individual handedness. PloS one12 11: 1-25. doi:10.1371/journal.pone.0184343

UAS stealth: target pursuit at constant distance using a bio-inspired motion camouflage guidance law
Strydom, Reuben and Srinivasan, Mandyam V. (2017) UAS stealth: target pursuit at constant distance using a bio-inspired motion camouflage guidance law. Bioinspiration and Biomimetics, . doi:10.1088/1748-3190/aa7d65

A strategy for mid-air collision avoidance: Speed modulation to increase minimum separation using a mutually independent and mutually beneficial technique
D. Gunasinghe and M.V. Srinivasan (2017) A strategy for mid-air collision avoidance: Speed modulation to increase minimum separation using a mutually independent and mutually beneficial technique. Paper 139, Proceedings, 2017 IEEE International Conference on Robotics and Biomimetics, Macau SAR, China.

Neural basis of forward flight control and landing in honeybees
Ibbotson, M R, Hung, Y-S, Meffin, H, Boeddeker, N and Srinivasan, M V (2017) Neural basis of forward flight control and landing in honeybees. Scientific reports7 1: 1-15. doi:10.1038/s41598-017-14954-0

A generalized algorithm for tuning UAS flight controllers
H. Wright, R. Strydom and M.V. Srinivasan (2018) A generalized algorithm for tuning UAS flight controllers.  Proceedings, 2018 International Conference on Unmanned Aircraft Systems, Dallas, Tx, USA,  June 12-15.

A mid-air collision warning system: Performance comparison using simulated ADS-B, radar and vision sensor inputs
D. Gunasinghe, K.K.K. Lawson, R. Strydom and M.V. Srinivasan (2018) A mid-air collision warning system: Performance comparison using simulated ADS-B, radar and vision sensor inputs. Proceedings, 2018 International Conference on Unmanned Aircraft Systems, Dallas, Tx, USA,  June 12-15.

Vision-only egomotion estimation in 6DOF using a sky compass
T. Jouir, R. Strydom, T.M. Stace and M.V. Srinivasan (2018) Vision-only egomotion estimation in 6DOF using a sky compass. Robotica 36, 1571-1589.

Effects of cold anaesthesia on the defensive behaviour of honeybees
Groening, J., Venini, D. and Srinivasan, M. V. (2018) Effects of cold anaesthesia on the defensive behaviour of honeybees. Insectes Sociaux, . doi:10.1007/s00040-018-0620-0


Strategies for mid-air collision avoidance in aircraft: lessons from bird flight
(2014–2017) ARC Linkage Projects

From flying animals to airborne machines and back
(2012–2018) Vice-Chancellor's Senior Research Fellowship


  • Marie Dacke, University of Lund: Honeybee navigation
  • Thomas Labhart, University of Zurich: Polarization vision in honeybee navigation
  • Jonathan Roberts, CSIRO, Brisbane: Robotics
  • Farid Kendoul, CSIRO, Brisbane:  Biologically inspired robotics
  • Tristan Perez, Queensland University of Technology: Control system dynamics