Prof. Sridhar Ravi Profile

Prof. Sridhar Ravi

at University of New South Wales

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Proceedings Article | 10 June 2024 Presentation

Gait control for undulatory swimmers: inspiration from biological systems to robots

Sridhar Ravi, Karthick Dhileep, Don Sofge, Qiuxiang Huang, Fangbao Tian, John Young, Joseph Lai

Proceedings Volume 13055, 1305506 (2024) https://doi.org/10.1117/12.3023805

KEYWORDS: Robots, Gait analysis, Robotic systems, Control systems, Kinematics, Robotics, Fluid dynamics, Wave propagation, Simulations, Particle image velocimetry

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Swimming animals display exceptional ability to move efficiently in aquatic environments and display a rich diversity of mechanisms for generating and controlling propulsive force. The swimming profile and performance of aquatic animals has been of interest to engineers, biologist, and roboticists alike. Among the different swimming modes, undulatory swimming is common across various animals such as fish and eels. In this swimming mode, traveling or stationary waves are generated over the body and the control of which results in the generation of propulsive force. What is the relationship between the waveforms and the fluid mechanic forces? We sought to answer this question by combining experiments on biological swimmers and computational fluid dynamics simulations. We found that various swimming gaits can be generated through modulation of simple parameterized model. A bio-inspired robotic model was developed to demonstrate and test the locomotion dynamics of the various gaits. The findings from this study pave the way for highly maneuverable swimming robots that exploit the interplay between body waves and fluid forces.

Proceedings Article | 30 May 2022 Presentation

Obstacle avoidance and navigation in honeybees

Sridhar Ravi, Fumin Zhang

Proceedings Volume PC12124, PC1212408 (2022) https://doi.org/10.1117/12.2634272

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Insects are well known to be adept at flying through cluttered natural environments. This ability to avoid collisions and control flight speed is an active field of interest for potential applications in unmanned aerial vehicles. Previous studies have shown that insects primarily rely on visual motion of the environment, known as optic flow, to perform flight manoeuvres such as course control, landing, terrain following, etc. Vision based flight behaviours of honeybees have been studied extensively in the past and have been explained in terms of either the optomotor response or the collision avoidance (centering) response. However, the strategies used for avoiding smaller objects in the frontal view field remain unclear. This study investigates the strategies being used by honeybees (Apis Milfera) to avoid such obstacles. This was done by performing behavioural experiments, where the bees were trained to fly in a tunnel and were then presented with cylindrical obstacles of six different sizes ranging from 25mm to 165mm. The flights were recorded using a GoPro camera and then digitised using Matlab. The digitised trajectories have then been analysed for cues such as retinal angle, relative retinal expansion velocity(RREV), optic flow, etc., to gain an insight into the visuo-motor strategies being implemented by honeybees to avoid these obstacles. Our findings, based on analysing major events during flight, such as the point of deceleration before the obstacle, the point of maximum curvature and the point where bees cross the obstacle, suggest a combination of RREV and optic flow based response to avoid these obstacles.

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