18064071. SENSOR PLUGIN ARCHITECTURE FOR GRID MAP simplified abstract (Robert Bosch GmbH)
Contents
- 1 SENSOR PLUGIN ARCHITECTURE FOR GRID MAP
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SENSOR PLUGIN ARCHITECTURE FOR GRID MAP - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Key Features and Innovation
- 1.6 Potential Applications
- 1.7 Problems Solved
- 1.8 Benefits
- 1.9 Commercial Applications
- 1.10 Prior Art
- 1.11 Frequently Updated Research
- 1.12 Questions about Autonomous Vehicle Control Systems
- 1.13 Original Abstract Submitted
SENSOR PLUGIN ARCHITECTURE FOR GRID MAP
Organization Name
Inventor(s)
Oliver F. Schwindt of Sunnyvale CA (US)
Stephan Reuter of Bavaria (DE)
Christos Zalidis of Mountain View CA (US)
Tobias Berling of Sunnyvale CA (US)
SENSOR PLUGIN ARCHITECTURE FOR GRID MAP - A simplified explanation of the abstract
This abstract first appeared for US patent application 18064071 titled 'SENSOR PLUGIN ARCHITECTURE FOR GRID MAP
Simplified Explanation
The patent application describes systems and methods for controlling an autonomous vehicle using a multi-layer grid and sensor plugins. The system integrates sensor information into the grid to control vehicle movement.
- The system includes an electronic processor and memory storing a multi-layer grid and sensor plugins.
- Sensors output information, which is processed and integrated into the grid based on plausibility.
- The system controls vehicle movement based on the integrated sensor information.
Key Features and Innovation
- Utilizes a multi-layer grid to store information associated with positions in the environment.
- Generates sensor plugins based on sensor modality for integration into the grid.
- Controls vehicle movement based on integrated sensor information.
Potential Applications
The technology can be applied in various industries such as autonomous vehicles, robotics, and smart transportation systems.
Problems Solved
- Efficiently controls an autonomous vehicle by integrating sensor information into a multi-layer grid.
- Enhances the accuracy and reliability of vehicle movement based on sensor data.
Benefits
- Improved control and navigation of autonomous vehicles.
- Enhanced safety and efficiency in transportation systems.
- Increased reliability and accuracy in decision-making processes.
Commercial Applications
Title: Autonomous Vehicle Control System This technology can be utilized in autonomous vehicles for transportation companies, logistics companies, and smart city initiatives to improve efficiency and safety in transportation systems.
Prior Art
Readers can explore prior research on autonomous vehicle control systems, sensor integration in autonomous vehicles, and grid-based navigation systems.
Frequently Updated Research
Stay updated on advancements in autonomous vehicle technology, sensor integration, and grid-based navigation systems for the latest innovations in autonomous vehicle control.
Questions about Autonomous Vehicle Control Systems
How does the integration of sensor information into a multi-layer grid improve autonomous vehicle control?
Integrating sensor information into a multi-layer grid enhances the accuracy and reliability of vehicle movement by providing a comprehensive view of the environment.
What are the potential challenges in implementing sensor plugins in autonomous vehicles?
Implementing sensor plugins in autonomous vehicles may face challenges related to sensor compatibility, data processing, and real-time integration into the control system.
Original Abstract Submitted
Systems and methods for controlling an autonomous vehicle. One system includes an electronic processor and a memory configured to store a multi-layer grid and a multi-instanceable sensor plugin. The multi-layer grid includes information associated with positions in the environment. A plurality of sensors are configured to output sensor information. The electronic processor is configured to, for each of the plurality of sensors, determine a modality of the sensor and generate an instance of the sensor plugin based on the modality. The electronic processor receives, processes, and determines a plausibility of the sensor information. In response to determining that the sensor information is plausible, the electronic processor integrates the sensor information to the multi-layer grid. The electronic processor controls vehicle movement based on the multi-layer grid.
