Mobile Robot Road Crossing Using Dynamic Collision Timing
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Solution Overview
Problem
Existing methods for mobile robots to cross roads autonomously face challenges in safely navigating dynamic obstacles, particularly moving vehicles, due to uncertainties in obstacle trajectories and lack of human intervention, leading to potential collisions and reduced autonomy.
Innovation Solution
A road crossing method for mobile robots that includes a data processing unit to estimate the location and time of collision with dynamic objects, generating control commands to avoid collisions by detecting and classifying objects, predicting their trajectories, and adjusting the robot's path or speed, using sensors like cameras, radar, and LIDAR to gather data for accurate obstacle detection and trajectory estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If motion planning algorithms are used to calculate safe paths avoiding static objects, then collision avoidance with static obstacles is improved, but the system cannot handle moving objects that may intersect the planned path during operation
Solution Approach 1:
The system transforms static motion planning into dynamic motion planning by continuously updating the configuration space with current positions of moving objects. The motion planning algorithm recalculates paths in real-time based on updated environmental data, allowing the robot to adapt its trajectory dynamically rather than following a pre-calculated static path.
Solution Approach 2:
The system implements continuous feedback loops where sensor data from moving objects is fed back to the motion planning module. This feedback mechanism allows the system to detect changes in the environment and adjust the robot's motion accordingly, ensuring collision avoidance with dynamic obstacles while maintaining efficient navigation.
2Reliability
If the robot waits for moving obstacles to pass to avoid collisions, then collision avoidance is improved, but operation time and energy consumption increase
Solution Approach 1:
The system performs preliminary calculations of potential collision points and trajectories before the robot reaches them. By predicting future positions of moving objects and pre-computing alternative paths, the robot can proactively adjust its motion to avoid collisions without unnecessary waiting, thereby maintaining operational efficiency while ensuring safety.
3Measurement precision
If multiple sensors are used to detect moving objects and predict trajectories, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system merges data from multiple sensor types (cameras, LIDAR, radar) into a unified environmental model. By integrating information from different sensors and fusing their data streams, the system achieves accurate trajectory estimation for moving objects while managing complexity through coordinated sensor operation rather than independent processing of each sensor.
Solution Approach 2:
The sensor system is designed with multi-functionality where the same sensor array serves multiple purposes: detecting static obstacles, tracking moving objects, estimating trajectories, and providing depth information. This universal approach reduces overall system complexity compared to having dedicated specialized sensors for each function.
Data Source
Figure 1a~1b
Figure 2(a)~2(d)
Figure 2e
AI summary
The present invention relates to a road crossing method for a mobile robot. The road crossing method comprises the step of the mobile robot approaching a road crossing. Further, the road crossing method comprises estimating with a data processing unit a location and time of collision with at least one dynamic object on the road crossing. Further still, the road crossing method comprises generating with the data processing unit control commands for the mobile robot to avoid collision with the at least one dynamic object based on the estimated location and time of collision with the at least one dynamic object. In addition, the present invention relates to a mobile robot comprising the data processing unit and configured to carry out the road crossing method. In a further aspect, the present invention relates to a positioning method for a wheeled mobile robot positioned on a sloped terrain, comprising the step of the mobile robot performing at least one maneuver for minimizing a magnitude of an acceleration vector of the mobile robot due to the gravity force acting on the mobile robot. In addition, the present invention relates to a mobile robot configured to carry out the positioning method.