Figure 3 - uploaded by Juxi Leitner
Content may be subject to copyright.
![28. Model of a human brain cell (neuron, A) and an artificial neuron (B) used in Artificial Neural Networks (ANNs). (Image taken from Maltarollo et al. [2013])](profile/Juxi-Leitner/publication/314761683/figure/fig21/AS:471217464451078@1489358406604/Model-of-a-human-brain-cell-neuron-A-and-an-artificial-neuron-B-used-in-Artificial.png)
28. Model of a human brain cell (neuron, A) and an artificial neuron (B) used in Artificial Neural Networks (ANNs). (Image taken from Maltarollo et al. [2013])
Source publication
Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein...
Citations
Design of a voice control 6DoF grasping robotic arm based on ultrasonic sensor, computer vision and Alexa voice assistance
We describe our software system enabling a tight integration between vision and control modules on complex, high-DOF humanoid robots. This is demonstrated with the iCub humanoid robot performing visual object detection, reaching and grasping actions. A key capability of this system is reactive avoidance of obstacle objects detected from the video stream while carrying out reach-and-grasp tasks. The subsystems of our architecture can independently be improved and updated, for example, we show that by using machine learning techniques we can improve visual perception by collecting images during the robot’s interaction with the environment. We describe the task and software design constraints that led to the layered modular system architecture.
