Robot Arm EV Charging Plug Insertion Using Modified Digital Maps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current autonomous charging systems for electric vehicles face challenges in quickly, reliably, and damage-free plugging of charging plugs into charging sockets, especially when visibility markers are obstructed or not supported by all systems, and digital maps require high computing effort for precise collision-free contact.
Innovation Solution
A method and apparatus using a programmable robot arm with a camera unit for camera-based localization, digitalizing the area with an octomap, modifying the map to remove the charging socket region, and plugging the charging plug based on trajectory calculations from the modified map, enabling precise and efficient plug-in without mechanical contact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If position markers are used at the charging socket for camera-based localization, then orientation precision is improved, but the system becomes vulnerable to visibility obstruction (snow, wear) and requires modifications to the charging socket
Solution Approach 1:
The patent removes position markers from the charging socket environment and extracts the localization function to the camera system itself. The camera unit on the charging robot autonomously identifies the charging socket through image processing and pattern recognition, eliminating the need for external markers that can be obscured or damaged.
Solution Approach 2:
The patent replaces the mechanical/optical marker system with a computational vision system. Instead of using physical position markers that require line-of-sight visibility, the system uses camera-based image analysis with algorithms that can identify charging sockets through their geometric and visual characteristics, substituting physical markers with digital image processing.
2Measurement precision
If a detailed digital map with small cubes is used for collision prevention, then positioning precision is improved, but computing effort increases significantly
Solution Approach 1:
The patent segments the environment into relevant and irrelevant regions. Instead of creating a detailed digital map of the entire surrounding area, the system focuses computational resources on localizing and navigating to the charging socket, using coarse environmental representation and refining detail only where necessary for the plug-in operation.
Solution Approach 2:
The patent applies partial action by using sufficient rather than excessive detail in the digital map. The system creates a digital representation that includes only the necessary information for collision-free navigation to the charging socket, avoiding the computational overhead of overly detailed voxel-based maps while maintaining adequate positioning precision.
3Reliability
If the charging robot approaches the charging socket directly without modifying the digital map, then collision prevention is improved, but the plug-in process becomes slower due to excessive caution
Solution Approach 1:
The patent performs preliminary actions by planning the trajectory in advance using the digital map to identify collision-free paths. The charging robot calculates and executes a pre-planned approach trajectory that avoids obstacles, then transitions to a controlled plug-in phase where the charging socket region is temporarily removed from collision detection, allowing faster final approach without sacrificing overall safety.
Solution Approach 2:
The patent dynamically adjusts the collision detection parameters during the plug-in process. The digital map is modified in real-time by removing the charging socket region from collision constraints, allowing the robot to accelerate during the final approach phase while maintaining collision prevention for all other areas, creating a dynamic balance between safety and speed.
4Measurement precision
If visibility markers are used for camera-based localization, then localization accuracy is improved, but the system requires modifications to the charging socket and markers can be obscured by environmental factors
Solution Approach 1:
The patent extracts the localization functionality from the charging socket infrastructure and relocates it to the mobile charging robot. Instead of requiring the charging socket to have embedded markers or modified features, the robot equips itself with a camera unit and image processing capabilities to autonomously identify and locate charging sockets through their inherent visual characteristics.
Solution Approach 2:
The patent uses digital copying of the charging socket's visual appearance and geometric features to create a recognizable target for the camera system. By capturing and processing images of the charging socket, the system creates a digital representation that can be matched and identified without requiring physical markers, effectively copying the identification function from the environment to the robot's sensor system.
Data Source
AI summary
Technologies and techniques for autonomously plugging a charging plug into a charging socket of a vehicle, wherein the charging plug is installed on a programmable robot arm of a charging station. A camera is used to locate the charging socket using image analysis of acquired images of the charging socket and the surroundings of the charging station are represented as a digital map including a charging socket region in which the charging socket is located. The charging plug is moved into a plug-in position at a distance from the charging socket and the digital map is processed into a modified digital map having a remote charging socket region. A plugging-in operation is then performed based on the modified digital map.