Mobile robot range sensing through visual looming

This article describes and evaluates visual looming as a monocular range sensing method for mobile robots. The looming algorithm is based on the relationship between the displacement of a camera relative to an object, and the resulting change in the size of the object's image on the focal plane of the camera. We have carried out systematic experiments to evaluate the ranging accuracy of the looming algorithm using a Pioneer 1 mobile robot equipped with a color camera. We have also performed noise sensitivity for the looming algorithm, obtaining theoretical error bounds on the range estimates for given levels of odometric and visual noise, which were verified through experimental data. Our results suggest that looming can be used as a robust, inexpensive range sensor as a complement to sonar.


Visual Looming as a range sensor for mobile robots
Şahin, Erol (1998-01-01)
This paper describes and evaluates visual looming as a method for monocular range estimation. The looming algorithm is based on the relationship between displacements of the observer relative to an object, and the resulting change in the size of the object's image on the focal plane of the camera. Though the looming algorithm has been described in detail in prior reports, its usefulness for inexpensive, robust ranging has not been realized widely. In this paper we analyze visual looming as a visual range se...
Robot mimicking: A visual approach for human machine interaction
Uskarci, A; Alatan, Abdullah Aydın; Dindaroglu, MS; Ersak, A (2003-01-01)
The proposed method is the preliminary step for a human-machine interaction system, in which a robot arm mimics the movements of a human arm, visualized through a camera set-up. In order to achieve this goal, the posture of a model joint, which simulates a human arm, is determined by finding the bending and yaw angles from captured images. The image analysis steps consist of preprocessing of noise via median filtering, thresholding and connected component analysis. The relation between the relative position...
A laterally resonating gravimetric sensor with uniform mass sensitivity and high linearity
Eroglu, D.; Bayraktar, E.; Külah, Haluk (2011-09-01)
In this paper, a laterally resonating gravimetric sensor with high linearity and uniform mass sensitivity is presented for biochemical sensor applications including rare-cell detection. The sensor utilizes symmetrically placed, balanced, folded spring beam structures to ensure lateral motion of the proof mass and limit the displacement difference between the proof mass center and edges. The dynamic mass sensitivity range of the resonator is increased by using the above mentioned properties of the resonators...
A composite pulsating controller for achieving high-performance positioning
Tufekci, C. S.; Craig, K. C. (SAGE Publications, 2012-02-01)
A non-linear robust control algorithm called a composite pulsating controller (CPC), which attains high-performance positioning specifications, is presented. The CPC is designed specifically for real product applications that have certain limitations such as friction, motor sizing, amplifier saturation, computational power and like. The CPC is composed of a bang-bang controller, a nominal proportional-integral-derivative (PID) controller, a high-gain PID controller and a pulsating controller in accomplishin...
Modeling Self-Organized Aggregation in Swarm Robotic Systems
Bayindir, Levent; Şahin, Erol (2009-04-02)
In this paper, we propose a model for the self-organized aggregation of a swarm of mobile robots. Specifically, we use a simple probabilistic finite state automata (PFSA) based aggregation behavior and analyze its performance using both a point-mass and a physics-based simulator and compare the results against the predictions of the model. The results show that the probabilistic model predictions match simulation results and PFSA-based aggregation behaviors with fixed probabilities are unable to generate sc...
Citation Formats
E. Şahin, “Mobile robot range sensing through visual looming,” 1998, Accessed: 00, 2020. [Online]. Available: