18436684. SYSTEM AND METHODS FOR PIXEL BASED MODEL PREDICTIVE CONTROL simplified abstract (GOOGLE LLC)
Contents
- 1 SYSTEM AND METHODS FOR PIXEL BASED MODEL PREDICTIVE CONTROL
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SYSTEM AND METHODS FOR PIXEL BASED MODEL PREDICTIVE CONTROL - 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 Unanswered Questions
- 1.11 Original Abstract Submitted
SYSTEM AND METHODS FOR PIXEL BASED MODEL PREDICTIVE CONTROL
Organization Name
Inventor(s)
Danijar Hafner of Toronto (CA)
SYSTEM AND METHODS FOR PIXEL BASED MODEL PREDICTIVE CONTROL - A simplified explanation of the abstract
This abstract first appeared for US patent application 18436684 titled 'SYSTEM AND METHODS FOR PIXEL BASED MODEL PREDICTIVE CONTROL
Simplified Explanation
The patent application describes techniques for model predictive control of a robot using a latent dynamics model and a reward function. The latent space can be divided into deterministic and stochastic portions to generate likely robot trajectories based on the model.
- The patent enables model predictive control of a robot based on a latent dynamics model and a reward function.
- The latent space can be divided into deterministic and stochastic portions for generating likely robot trajectories.
- Multiple reward functions can be used, each corresponding to a different robot task.
Potential Applications
This technology could be applied in various fields such as industrial automation, autonomous vehicles, robotic surgery, and smart manufacturing.
Problems Solved
1. Improved control and optimization of robot movements. 2. Enhanced efficiency and performance of robotic systems.
Benefits
1. Increased accuracy and precision in robot control. 2. Enhanced adaptability to different robot tasks. 3. Improved overall productivity and operational efficiency.
Potential Commercial Applications
Optimized Robot Control for Industrial Automation
Possible Prior Art
Prior art related to model predictive control, latent dynamics models, and reward functions in robotics could be relevant to this patent application.
Unanswered Questions
1. What specific industries or sectors could benefit the most from this technology? 2. Are there any limitations or constraints in implementing this model predictive control system in real-world robotic applications?
Original Abstract Submitted
Techniques are disclosed that enable model predictive control of a robot based on a latent dynamics model and a reward function. In many implementations, the latent space can be divided into a deterministic portion and stochastic portion, allowing the model to be utilized in generating more likely robot trajectories. Additional or alternative implementations include many reward functions, where each reward function corresponds to a different robot task.
