Professor Srini Srinivasan

Professorial Research Fellow

Queensland Brain Institute

Professor

School of Information Technology and Electrical Engineering
Faculty of Engineering, Architecture and Information Technology
m.srinivasan@uq.edu.au
+61 7 334 66322

Overview

Srinivasan's research focuses on the principles of visual processing, perception and cognition in simple natural systems, and on the application of these principles to machine vision and robotics.

He holds an undergraduate degree in Electrical Engineering from Bangalore University, a Master's degree in Electronics from the Indian Institute of Science, a Ph.D. in Engineering and Applied Science from Yale University, a D.Sc. in Neuroethology from the Australian National University, and an Honorary Doctorate from the University of Zurich. Srinivasan is presently Professor of Visual Neuroscience at the Queensland Brain Institute and the School of Information Technology and Electrical Engineering of the University of Queensland. Among his awards are Fellowships of the Australian Academy of Science, of the Royal Society of London, and of the Academy of Sciences for the Developing World, the 2006 Australia Prime Minister’s Science Prize, the 2008 U.K. Rank Prize for Optoelectronics, the 2009 Distinguished Alumni Award of the Indian Institute of Science, and the Membership of the Order of Australia (AM) in 2012.

Research Interests

  • Vision and navigation in animals and machines
    Srinivasan's research focuses on the principles of visual processing, perception and cognition in simple natural systems, and on the application of these principles to machine vision and robotics.

Research Impacts

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. These 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 have led 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.

Qualifications

  • Master of Philosophy, Yale University
  • Fellow, Australian Academy of Science
  • Bachelor of Electrical Engineering (Honours), B'Lore
  • Masters in Applied Electronics & Servomechanisms, IISC
  • Doctorate of Philosophy, Yale University

Publications

View all Publications

Supervision

View all Supervision

Available Projects

  • Using high speed cameras, we are investigating how birds (budgerigars) use visual information to control speed and measure the distance they have flown. The birds are subjected to moving patterns projected onto the side walls of a 25 m long tunnel, allowing direct manipulation of the visual cues that they perceive in flight. This project is part of an international collaboration with scientists from Stanford and the University of British Columbia.

  • In cooperation with Boeing and scientists from the University of Newcastle we are investigating the ability of birds to avoid mid air collisions, when facing incoming obstacles or other birds. The aim of this study is to gain a better understanding of how birds manage to avoid such collisionsand derive simple rules for collision avoidance that would enhance the safety of commercial air travel.

  • Using a wind tunnel that can provide headwinds and tail winds as well as optic flow stimulation, we are preparing to investigate the cues that control flight speed and the streamlining of the body during free flight. This study will involve video-filming trained bees flying through the tunnel to a food reward, under various stimulus conditions.

View all Available Projects

Publications

Book

  • Flying insects and robots. Edited by Floreano, Dario, Zufferey, Jean-Christophe, Srinivasan, Mandyam V. and Ellington, charlie Heidelberg, Germany ; New York, U.S.A.: Springer, 2010.

Book Chapter

  • Srinivasan, Mandyam V., Moore, Richard J. D., Thurrowgood, Saul, Soccol, Dean, Bland, Daniel and Knight, Michael (2014). Vision and Navigation in Insects, and Applications to Aircraft Guidance. In John S. Werner and Leo M. Chalupa (Ed.), The new visual neuroscience (pp. 1219-1229) Cambridge, Massachusett: The MIT Press.

  • Srinivasan, Mandyam V. (2012). Bee learning and communication. In N. M. Seel (Ed.), Encyclopedia of the sciences of learning (pp. 418-421) United States of America: Springer. doi:10.1007/978-1-4419-1428-6_972

  • Srinivasan, Mandyam V., Moore, Richard, Thurrowgood, Saul, Soccol, Dean and Bland, Daniel (2012). From biology to engineering: insect vision and application to robotics. In Friedrich G. Barth, Joseph A. C. Humphrey and Mandyam V. Srinivasan (Ed.), Frontiers in sensing: from biology to engineering (pp. 19-39) Lahnau, Germany: Springer.

  • Moore, Richard J. D., Thurrowgood, Saul, Soccol, Dean, Bland, Daniel and Srinivasan, Mandyam V. (2011). A bio-inspired stereo vision system for guidance of autonomous aircraft. In Asim Bhatti (Ed.), Advances in theory and applications of stereo vision (pp. 305-326) Rijeka, Croatia: InTech.

  • Srinivasan, Mandyam V., Thurrowgood, Saul and Soccol, Dean (2010). MAV guidance inspired by priniciples of insect vision. In Richard Blockley and Wei Shyy (Ed.), Encyclopedia of Aerospace Engineering (pp. x-x) Hoboken, NJ, United States: John Wiley & Sons. doi:10.1002/9780470686652.eae410

  • Srinivasan, Mandyam V., Thurrowgood, Saul and Soccol, Dean (2009). From Visual Guidance in Flying Insects to Autonomous Aerial Vehicles. In Dario Floreano, Jean-Christophe Zufferey, Mandyam V. Srinivasan and Charlie Ellington (Ed.), Flying insects and robots (pp. 15-28) Heidelberg & Berlin: Springer-Verlag Berlin Heidelberg. doi:10.1007/978-3-540-89393-6_2

  • Reinhard, Judith and Srinivasan, Mandyam V. (2009). The role of scents in honey bee foraging and recruitment. In Stefan Jarau and Michael Hrncir (Ed.), Food Exploitation by Social Insects: Ecological, Behavioral, and Theoretical Approaches (pp. 165-182) Boca Raton, USA: CRC Press.

  • Srinivasan, Mandyam and Reinhard, Judith (2008). Bees: Beyond the honey. In J. Davies and I. Hansen (Ed.), The Finlay Lloyd book about animals (pp. 25-38) Braidwood, N.S.W., Australia: Finlay Lloyd Publishing.

  • Srinivasan, Mandyam, Zhang, Shaowu and Reinhard, Judith (2006). Small brains, smart minds: vision, perception, navigation and 'cognition' in insects. In Eric Warrant and Dan-Eric Nilsson (Ed.), Invertebrate Vision (pp. 462-493) Cambridge & New York: Cambridge University Press.

  • Zhang, S. W. and Srinivasan, M, V. (2004). Exploration of cognitive capacity in honeybees. In Frederick R. Prete (Ed.), Complex worlds from simpler nervous systems (pp. 41-74) Cambridge Mass: MIT Press.

  • Srinivasan, M. V. and Zhang, S. W. (2004). Motion Cues in Insect Vision and Navigation. In L. M. Chalupa and J. S. Werner (Ed.), The Visual Neurosciences (pp. 1193-1202) Cambridge, Mass.: MIT Press.

  • Zhang, S. W. and Srinivasan, M. V. (2004). Visual Perception and Cognition in Honeybees. In L. M. Chalupa and J. S. Werner (Ed.), The Visual Neurosciences (pp. 1501-1513) Cambridge, Mass.: MIT Press.

  • Wehner, R. and Srinivasan, M. V. (2003). Path Integration in Insects. In K. K. Jeffrey (Ed.), The neurobiology of spatial behaviour (pp. 9-30) Oxford: Oxford University Press.

  • Srinivasan, M. V. (1989). Motion sensitivity in insect vision: roles and neural mechanisms. In R. Naresh Singh and N. J. Strausfeld (Ed.), Neurobiology of Sensory Systems (pp. 97-106) New York: Plenum Press.

Journal Article

Conference Publication

  • 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

  • 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, The University of Queensland, (). 5-7 December 2016.

  • 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

  • Jouir, Tasarinan, Strydom, Reuben and Srinivasan, Mandyam V. (2015). A 3D sky compass to achieve robust estimation of UAV attitude. In: ACRA 2015. Australasian Conference on Robotics and Automation (ACRA 2015), Canberra, ACT, Australia, (). 2-4 December 2015.

  • Denuelle, Aymeric, Thurrowgood, Saul, Kendoul, Farid and Srinivasan, Mandyam V. (2015). A view-based method for local homing of unmanned rotorcraft. In: Donald Bailey, G. Sen Gupta and Serge Demidenko, Proceedings of the 2015 6th International Conference on Automation, Robotics and Applications, ICARA 2015. 6th International Conference on Automation, Robotics and Applications, Queenstown, New Zealand, (443-449). 17-19 February 2015. doi:10.1109/ICARA.2015.7081189

  • Denuelle, Aymeric and Srinivasan, Mandyam V. (2015). Bio-inspired visual guidance: from insect homing to UAS navigation. In: 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE International Conference on Robotics and Biomimetics, Zuhai, China, (326-332). 6-9 December 2015. doi:10.1109/ROBIO.2015.7418788

  • Strydom, Reuben, Singh, Surya P. N. and Srinivasan, Mandyam V. (2015). Biologically inspired interception: a comparison of pursuit and constant bearing strategies in the presence of sensorimotor delay. In: 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE International Conference on Robotics and Biomimetics, Zhuhai, China, (2442-2448). December 6-9, 2015. doi:10.1109/ROBIO.2015.7419705

  • Denuelle, Aymeric, Thurrowgood, Saul, Strydom, Reuben, Kendoul, Farid and Srinivasan, Mandyam V. (2015). Biologically-inspired visual stabilization of a rotorcraft UAV in unknown outdoor environments. In: 2015 International Conference on Unmanned Aircraft Systems (ICUAS'15) : final program and book of abstracts. 2015 International Conference on Unmanned Aircraft Systems, ICUAS 2015, Denver, CO United States, (1084-1093). 9-12 June 2015. doi:10.1109/ICUAS.2015.7152400

  • Wang, Haibo, Kurniawati, Hanna, Singh, Surya and Srinivasan, Mandyam (2015). In-silico behavior discovery system: an application of planning in ethology. In: Ronen Brafman, Carmel Domshlak, Patrik Haslum and Shlomo Zilberstein, Proceedings of the Twenty-Fifth International Conference on Automated Planning and Scheduling (ICAPS 2015). International Conference on Automated Planning and Scheduling (ICAPS), Jerusalem, Israel, (296-304). 7-11 June 2015.

  • Denuelle, Aymeric, Strydom, Reuben and Srinivasan, Mandyam V. (2015). Snapshot-based control of UAS hover in outdoor environments. In: 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE International Conference on Robotics and Biomimetics, Zuhai, China, (1278-1284). 6-9 December 2015. doi:10.1109/ROBIO.2015.7418947

  • Denuelle, Aymeric and Srinivasan, Mandyam V. (2015). Snapshot-based navigation for the guidance of UAS. In: Australasian Conference on Robotics and Automation (ACRA 2015). Australasian Conference on Robotics and Automation, Canberra, ACT, Australia, (). 2-4 December 2015.

  • Strydom, Reuben, Thurrowgood, Saul and Srinivasan, Mandyam V. (2015). TCM: A fast technique to determine if an object is moving or stationary from a UAV. In: ACRA 2015. Australasian Conference on Robotics and Automation (ACRA 2015), Canberra, ACT, Australia, (). 2-4 December 2015.

  • Strydom, Reuben, Thurrowgood, Saul, Denuelle, Aymeric and Srinivasan, Mandyam V. (2015). UAV guidance: a stereo-based technique for interception of stationary or moving targets. In: Clare Dixon and Karl Tuyls, Towards Autonomous Robotic Systems (Taros 2015). 16th Annual Conference on Towards Autonomous Robotic Systems (TAROS), Liverpool England, (258-269). 8 - 10 September 2015. doi:10.1007/978-3-319-22416-9_30

  • Strydom, Reuben, Thurrowgood, Saul and Srinivasan, Mandyam V. (2014). Visual odometry: autonomous UAV navigation using optic flow and stereo. In: Proceedings of the 2014 Australasian Conference on Robotics and Automation. ACRA2014: Australasian Conference on Robotics and Automation, Melbourne VIC, Australia, (). 2-4 December 2014.

  • Strydom, Reuben, Thurrowgood, Saul and Srinivasan, Mandyam V. (2013). Airborne vision system for the detection of moving objects. In: Proceedings of the 2013 Australasian Conference on Robotics & Automation. ACRA2013: Australasian Conference on Robotics and Automation, Kensington, NSW, Australia, (1-7). 2-4 December, 2013.

  • Wang, Haibo, Kurniawati, Hanna, Singh, Surya and Srinivasan, Mandyam (2013). Animal locomotion in silico: a POMDP-based tool to study mid-air collision avoidance strategies in flying animals. In: Proceedings of the 2013 Australasian Conference on Robotics & Automation. ACRA2013: Australasian Conference on Robotics and Automation, Kensington, NSW, Australia, (1-8). 2-4 December, 2013.

  • Baker, Samuel, Soccol, Dean, Postula, Adam and Srinivasan, Mandyam (2013). Passive landing gear using coupled mechanical design. In: Proceedings of the 2013 Australasian Conference on Robotics & Automation. ACRA2013: Australasian Conference on Robotics and Automation, Kensington, NSW, Australia, (1-8). 2-4 December, 2013.

  • Nourani-Vatani, Navid, Borges, Paulo V. K., Roberts, Jonathan M. and Srinivasan, Mandyam V. (2012). Topological localization using optical flow descriptors. In: Proceedings of the IEEE International Conference on Computer Vision. 2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011, Barcelona, Spain, (1030-1037). 6-13 November 2011. doi:10.1109/ICCVW.2011.6130364

  • Moore, Richard J. D., Thurrowgood, Saul and Srinivasan, Mandyam V. (2012). Vision-only estimation of wind field strength and direction from an aerial platform. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012) - Proceedings. 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012), Vilamoura, Algarve, Portugal, (4544-4549). 7-12 October 2012. doi:10.1109/IROS.2012.6385682

  • Moore, Richard J. D., Thurrowgood, Saul, Bland, Daniel, Soccol, Dean and Srinivasan, Mandyam V. (2011). A fast and adaptive method for estimating UAV attitude from the visual horizon. In: Nancy M. Amato, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems proceedings. 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco, CA, United States, (4935-4940). 25-30 September 2011. doi:10.1109/IROS.2011.6048314

  • Moore, Richard J. D., Thurrowgood, Saul, Soccol, Dean, Bland, Daniel and Srinivasan, Mandyam V. (2011). A method for the visual estimation and control of 3-DOF attitude for UAVs. In: ACRA 2011 Proceedings. Australasian Conference on Robotics and Automation (ACRA 2011), Melbourne, Australia, (1-9). 7-9 December 2011.

  • Fernandes, Joshua, Postula, Adam, Thurrowgood, Saul and Srinivasan, Mandayam (2011). Insect inspired vision for micro aerial vehicle navigation. In: Tom Drummond and Wai Ho Li, ACRA 2011 Proceedings. Australasian Conference on Robotics and Automation 2011, Melbourne, Australia, (1-8). 7-9 December 2011.

  • Luu, Tien, Cheung, Allen, Ball, David and Srinivasan, Mandyam (2010). Honeybee flight: a novel 'streamlining' response. In: 9th International Congress on Neuroethology, Salamanca, Spain, (356-356). 2 - 7 August 2010.

  • Sturzl, Wolfgang and Srinivasan, Mandyam V. (2010). Omnidirectional imaging system with constant elevational gain and single viewpoint. In: OMNIVIS 2010: The 10th Workshop on Omnidirectional Vision, Camera Networks and Non-classical Cameras. OMNIVIS 2010, Zaragoa, Spain, (1-7). 27 June 2010.

  • Moore, Richard J. D., Thurrowgood, Saul, Bland, Daniel, Soccol, Dean and Srinivasan, Mandyam V. (2010). UAV altitude and attitude stabilisation using a coaxial stereo vision system. In: 2010 IEEE International Conference on Robotics and Automation (ICRA). IEEE International Conference on Robotics and Automation (ICRA), Anchorage, AK, U.S.A., (29-34). 3-8 May 2010. doi:10.1109/ROBOT.2010.5509465

  • Thurrowgood, Saul, Moore, Richard J. D., Bland, Daniel, Soccol, Dean and Srinivasan, Mandyam V. (2010). UAV attitude control using the visual horizon. In: Gordon Wyeth and Ben Upcroft, Proceedings of the 2010 Australasian Conference on Robotics & Automation. Australasian Conference on Robotics and Automation 2010 (ACRA 2010), Brisbane, QLD, Australia, (). 1-3 December 2010.

  • Moore, R. J. D., Thurrowgood, S., Bland, D., Soccol, D. and Srinivasan, M. V. (2009). A stereo vision system for UAV guidance. In: Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems. The 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, Missouri, USA, (3386-3391). 11-15 October, 2009. doi:10.1109/IROS.2009.5354152

  • Thurrowgood, Saul, Soccol, Dean, Moore, Richard J. D, Bland, Daniel and Srinivasan, Mandyam V. (2009). A vision based system for attitude estimation of UAVs. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, United States, (5725-5730). 11-15 October 2009. doi:10.1109/IROS.2009.5354041

  • Nourani-Vatani, Navid, Roberts, Jonathan and Srinivasan, Mandiam V. (2009). Practical visual odometry for car-like vehicles. In: Proceedings, 2009 IEEE International Conference on Robotics and Automation. IEEE International Conference on Robotics and Automation. ICRA2009, Kobe, Japan, (3551-3557). 12-17 May 2009. doi:10.1109/ROBOT.2009.5152403

  • Srinivasan, M. V. and Reinhard, J. (2008). A visual strategy for landing on a vertical surface. In: 2008 IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS 2008), Nice, France, (). 22-26 September 2008.

  • Nourani-Vatani, Navid, Roberts, Jonathan and Srinivasan, Mandyam V. (2008). IMU aided 3D visual odometry for car-like vehicles. In: Proceedings of the 2008 Australasian Conference on Robotics & Automation. ACRA 2008: 10th Australasian Conference on Robotics & Automation (ACRA), Canberra, ACT, Australia, (1-8). 3-5 December 2008.

  • Thurrowgood, Saul, Stuerzl, Wolfgang, Soccol, Dean and Srinivasan, Mandyam (2007). A panoramic stereo imaging system for aircraft guidance. In: Matthew Dunbabin and Mandyam Srinivasan, Proceedings of 2007 Australasian Conference on Robotics & Automation. Australasian Conference on Robotics and Automation 2007, Brisbane, Australia, (). 10-12 December 2007.

  • Soccol, Dean, Thurrowgood, Saul and Srinivasan, Mandyam (2007). A vision system for optic-flow-based guidance of UAVs. In: Matthew Dunbabin and Mandyam Srinivasan, Proceedings of the 2007 Australasian Conference on Robotics & Automation. Australasian Conference on Robotics and Automation 2007, Brisbane, Australia, (). 10-12 December 2007.

  • Cheung, A., Zhang, S., Stricker, C. and Srinivasan, M. V. (2007). Animal navigation: Pitfalls and remedies. In: Proceedings of the Annual Meeting - Institute of Navigation. The 63rd Annual Meeting of the Institute of Navigation, Cambridge, MA, U.S.A., (270-279). 23- 25 April, 2007.

  • McCarthy, Chris, Barnes, Nick and Srinivasan, Mandyam (2007). Real time biologically-inspired depth maps from spherical flow. In: 2007 IEEE International Conference on Robotics and Automation. IEEE International Conference on Robotics and Automation 2007, Roma, Italy, (4887-4892). 10-14 April 2007. doi:10.1109/ROBOT.2007.364232

  • Srinivasan, M. V., Thurrowgood, S. and Soccol, D. (2006). An optical system for guidance of terrain following in UAVs. In: Video and Signal Based Surveillance 2006 (AVSS 2006). IEEE International Conference on Video and Signal Based Surveillance 2006 (AVSS 2006), Sydney, Australia, (51-56). 22-24 November 2006. doi:10.1109/AVSS.2006.23

  • Veeraraghavan, Ashok, Srinivasan, Mandyam, Chellappa, Rama, Baird, Emily and Lamont, Richard (2006). Motion based correspondence, for 3D tracking of multiple dim objects. In: 2006 IEEE International Conference on Acoustics, Speech and Signal Processing. 2006 IEEE International Conference on Acoustics, Speech and Signal Processing, Toulouse, France, (669-672). 14-19 May 2006. doi:10.1109/ICASSP.2006.1660431

  • Srinivasan, Mandyam V. (2006). Small brains, smart computations: Vision and navigation in honeybees, and applications to robotics. In: International Congress Series: 2nd International Conference on Brain-inspired Information Technology. Brain-Inspired IT II: Decision and Behavioral Choice, Hibikino, Kitakyushu, Japan, (30-37). 7-9 October, 2005. doi:10.1016/j.ics.2006.01.055

  • Baird, E., Srinivasan, M.V., Zhang, S.W., Lamont, R. and Cowling, A. (2006). Visual control of flight speed and height in the honeybee. In: Lecture Notes in Computer Science 4095. From Animals to Animats 9 9th International Conference on Simulation of Adaptive Behavior, SAB 2006,, Rome, Italy, (40-51). September 25-29, 2006.

  • Sturzl, W. and Srinivasan, M. V. (2005). Omnidirectional vision with frontal stereo. In: Pattern Recognition 27th DAGM Symposium. Pattern Recognition 27th DAGM Symposium, Vienna, Austria, (49-57). 31 Aug - 2 Sep 2005. doi:10.1007/11550518_7

  • Srinivasan, M. V. (2003). A new class of mirrors for wide-angle imaging. In: Computer Vision and Pattern Recognition Workshop 2003 (CVPRW 2003). Conference on Computer Vision and Pattern Recognition Workshop 2003 (CVPRW 2003), Madison, Wisconsin, U.S.A., (). 16-22 June 2003. doi:10.1109/CVPRW.2003.10069

  • Srinivasan, M. V., Zhang, S. W., Chahl, J. S. and Garratt, M.A. (2003). Landing strategies in honeybees, and applications to UAVs. In: Jarvis, R. and Zelinsky, A., Robotics research : the tenth international symposium. Robotics research : the tenth international symposium, xx, (373-384). xx.

  • Barrows, Geoffrey L., Chahl, Javaan S. and Srinivasan, Mandyam V. (2002). Biomimetic Visual Sensing and Flight Control. In: Proceedings Seventeenth International Unmanned Air Vehicle Systems Conference. Seventeenth International Unmanned Air Vehicle Systems Conference, Bristol, UK, (1-15). 8-10 April, 2002.

  • Wehner, R. and Srinivasan, M. V. (1984). The world as the insect sees it. In: Trevor Lewis, Insect communication : 12th symposium of the Royal Entomological Society of London. 12th symposium of the Royal Entomological Society of London, London, UK, (29-47). 7-9 September, 1983.

Other Outputs

  • Chahl, Javaan Singh and Srinivasan, Mandyam Veerambudi (2002). Imaging system. US Patent 6429418.

  • Chahl, Javaan Singh, Nagle, Martin Gerard, Srinivasan, Mandyam Veerambudi and Sobey, Peter John (1997). A novel system for panoramic video surveillance. WO95/06303.

Grants (Administered at UQ)

PhD and MPhil Supervision

Current Supervision

  • Doctor Philosophy — Principal Advisor

    Other advisors:

  • Doctor Philosophy — Principal Advisor

    Other advisors:

  • Doctor Philosophy — Principal Advisor

    Other advisors:

  • Doctor Philosophy — Principal Advisor

    Other advisors:

  • Doctor Philosophy — Principal Advisor

  • Doctor Philosophy — Associate Advisor

    Other advisors:

  • Doctor Philosophy — Associate Advisor

    Other advisors:

  • Doctor Philosophy — Associate Advisor

    Other advisors:

  • Master Philosophy — Associate Advisor

Completed Supervision

Possible Research Projects

Note for students: The possible research projects listed on this page may not be comprehensive or up to date. Always feel free to contact the staff for more information, and also with your own research ideas.

  • Using high speed cameras, we are investigating how birds (budgerigars) use visual information to control speed and measure the distance they have flown. The birds are subjected to moving patterns projected onto the side walls of a 25 m long tunnel, allowing direct manipulation of the visual cues that they perceive in flight. This project is part of an international collaboration with scientists from Stanford and the University of British Columbia.

  • In cooperation with Boeing and scientists from the University of Newcastle we are investigating the ability of birds to avoid mid air collisions, when facing incoming obstacles or other birds. The aim of this study is to gain a better understanding of how birds manage to avoid such collisionsand derive simple rules for collision avoidance that would enhance the safety of commercial air travel.

  • Using a wind tunnel that can provide headwinds and tail winds as well as optic flow stimulation, we are preparing to investigate the cues that control flight speed and the streamlining of the body during free flight. This study will involve video-filming trained bees flying through the tunnel to a food reward, under various stimulus conditions.

  • With the help of a specially designed bee flight tunnel, we are commencing an investigation to explore how bees avoid obstacles, and how they choose between alternative routes to ensure the safest (or quickest) route. This study will involve video-filming trained bees flying through the tunnel to a food reward, under various stimulus conditions.

  • We are investigating visual cues and other sensory cues that bees use to make smooth landings in the presence of wind. This study will involve video-filming bees as they land to reach a food reward, in the presence of wind coming in from different directions and at different speeds.

  • This Biorobotics project will involve embodying knowledge about vision and navigation in honeybees (biological compasses, visual odometry and patch integration) into a multirotor aircraft to enable it to locate virtual food sources, and navigate to them repeatedly and reliably.

  • This Biorobotics project will involve using the principles of optic flow analysis that the laboratory has gleaned from studying honeybee landings to develop and test algorithms that will enable rotorcraft to use vision to land autonomously in unstructured terrain.