scholarly journals Development of a Coaxial MAV with Real-Time Obstacle Avoidance Capability

2014 ◽  
Vol 1 (1) ◽  
pp. 18-30
Author(s):  
Abhishek Abhishek ◽  
◽  
Sagar Setu ◽  
Keyword(s):  
2009 ◽  
Vol 106 (37) ◽  
pp. 15996-16001 ◽  
Author(s):  
Christopher L. Striemer ◽  
Craig S. Chapman ◽  
Melvyn A. Goodale

When we reach toward objects, we easily avoid potential obstacles located in the workspace. Previous studies suggest that obstacle avoidance relies on mechanisms in the dorsal visual stream in the posterior parietal cortex. One fundamental question that remains unanswered is where the visual inputs to these dorsal-stream mechanisms are coming from. Here, we provide compelling evidence that these mechanisms can operate in “real-time” without direct input from primary visual cortex (V1). In our first experiment, we used a reaching task to demonstrate that an individual with a dense left visual field hemianopia after damage to V1 remained strikingly sensitive to the position of unseen static obstacles placed in his blind field. Importantly, in a second experiment, we showed that his sensitivity to the same obstacles in his blind field was abolished when a short 2-s delay (without vision) was introduced before reach onset. These findings have far-reaching implications, not only for our understanding of the time constraints under which different visual pathways operate, but also in relation to how these seemingly “primitive” subcortical visual pathways can control complex everyday behavior without recourse to conscious vision.


2013 ◽  
Vol 748 ◽  
pp. 695-698
Author(s):  
Hai Peng Wang ◽  
Yong Sun ◽  
Peng Xiao ◽  
Yi Qing Luan

The obstacle avoidance system is an important part of the intelligent inspection robot. According to the special environmental requirements for substation inspection robot, the inspection robot obstacle avoidance detection system was designed. The system takes MCU as the controller core, selects many sets of ultrasonic sensors to detect the obstacle information around the robot, designs the transmitting and receiving circuit of the ultrasonic signal, and completes the system software program. In consideration of the substations effect of EMI to the electronic equipments, when designing circuit, using a large of filter circuit, improve systems anti-interference performance, realize real-time and veracity of measurement. Using on substation shows that the system run steadily, have high measurement precision, its important for improving the robot using on substation.


Author(s):  
Tasher Ali Sheikh ◽  
Swacheta Dutta ◽  
Smriti Baruah ◽  
Pooja Sharma ◽  
Sahadev Roy

The concept of path planning and collision avoidance are two of the most common theories applied for designing and developing in advanced autonomous robotics applications. NI LabView makes it possible to implement real-time processor for obstacle avoidance. The obstacle avoidance strategy ensures that the robot whenever senses the obstacle stops without being collided and moves freely when path is free, but sometimes there exists a probability that once the path is found free and the robot starts moving, then within a fraction of milliseconds, the robot again sense the obstacle and it stops. This continuous swing of stop and run within a very small period of time may cause heavy burden on the system leading to malfunctioning of the components of the system. This paper deals with overcoming this drawback in a way that even after the robot calculates the path is free then also it will wait for a specific amount of time before running it. So as to confirm that if again the sensor detects the obstacle within that specified period then robot don’t need to transit its state suddenly thus avoiding continuous transition of run and stop. Thus it reduces the heavy burden on the system.


Robotica ◽  
1992 ◽  
Vol 10 (3) ◽  
pp. 217-227 ◽  
Author(s):  
Huang Han-Pang ◽  
Lee Pei-Chien

SUMMARYA real-time obstacle avoidance algorithm is proposed for autonomous mobile robots. The algorithm is sensor-based and consists of a H-mode and T-mode. The algorithm can deal with a complicated obstacle environment, such as multiple concave and convex obstacles. It will be shown that the algorithm is more efficient and more robust than other sensor-based algorithms. In addition, the algorithm will guarantee a solution for the obstacle avoidance problem. Since the algorithm only takes up a small computational time, it can be implemented in real time.


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