Nvidia corporation (20240157557). CONTROLLING A ROBOT DURING INTERACTION WITH A HUMAN simplified abstract
Contents
- 1 CONTROLLING A ROBOT DURING INTERACTION WITH A HUMAN
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 CONTROLLING A ROBOT DURING INTERACTION WITH A HUMAN - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
CONTROLLING A ROBOT DURING INTERACTION WITH A HUMAN
Organization Name
Inventor(s)
Sammy Joe Christen of Luzern (CH)
Wei Yang of Lake Forest Park WA (US)
Claudia Perez D'arpino of Seattle WA (US)
Yu-Wei Chao of Redmond WA (US)
CONTROLLING A ROBOT DURING INTERACTION WITH A HUMAN - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240157557 titled 'CONTROLLING A ROBOT DURING INTERACTION WITH A HUMAN
Simplified Explanation
The patent application describes apparatuses, systems, and techniques for controlling a real-world and/or virtual device, such as a robot, using neural networks. The device is controlled based on training the neural networks to control movement of agents with respect to targets while avoiding collisions with holders of the targets.
- Neural networks are used to control the movement of a device, such as a robot.
- The neural networks are trained to control the movement of agents towards targets while avoiding collisions with holders of the targets.
Potential Applications
This technology could be applied in various fields such as robotics, autonomous vehicles, and virtual reality simulations.
Problems Solved
This technology helps in efficiently controlling the movement of devices in real-world and virtual environments, ensuring safe and accurate navigation towards targets while avoiding collisions.
Benefits
The benefits of this technology include improved accuracy in controlling devices, enhanced safety measures to avoid collisions, and increased efficiency in achieving target objectives.
Potential Commercial Applications
One potential commercial application of this technology could be in the development of autonomous delivery robots for logistics companies.
Possible Prior Art
One possible prior art could be the use of neural networks in robotics for path planning and obstacle avoidance.
What are the specific neural network architectures used in this technology?
The specific neural network architectures used in this technology are not explicitly mentioned in the abstract. Further details may be provided in the full patent application.
How does this technology compare to traditional methods of controlling devices?
This technology offers a more advanced and adaptive approach to controlling devices compared to traditional methods. By utilizing neural networks, the device can learn and improve its movement strategies over time, leading to more efficient and effective navigation.
Original Abstract Submitted
apparatuses, systems, and techniques to control a real-world and/or virtual device (e.g., a robot). in at least one embodiment, the device is controlled based, at least in part on, for example, one or more neural networks. parameter values for the neural network(s) may be obtained by training the neural network(s) to control movement of a first agent with respect to at least one first target while avoiding collision with at least one stationary first holder of the at least one first target, and updating the parameter values by training the neural network(s) to control movement of a second agent with respect to at least one second target while avoiding collision with at least one non-stationary second holder of the at least one second target.
