Autonomous Robot Route Poses for Dynamic Obstacle Avoidance
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Solution Overview
Problem
Current robotic navigation systems struggle to make real-time adjustments to their planned paths in response to dynamic changes in the environment, such as blockages, leading to potential collisions or sub-optimal route adjustments.
Innovation Solution
The implementation of a robot system equipped with sensors to collect environmental data, create a map, determine route poses with repulsive and attractive forces, and perform interpolation to generate a collision-free path, allowing for dynamic route planning and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current robots follow a predetermined route, then the navigation path is simple to plan, but the robot cannot make real-time adjustments to avoid obstacles
Solution Approach 1:
The patent applies dynamics by transforming the static predetermined route into a dynamic path that can adapt in real-time. The route is represented as a sequence of poses that can be dynamically adjusted based on environmental changes. When obstacles are detected, the system dynamically modifies the route by adding new poses and adjusting existing ones, allowing the robot to navigate around obstacles while maintaining a structured approach to path planning.
Solution Approach 2:
The patent implements feedback mechanisms where sensor data about environmental changes (obstacles, dynamic objects) is continuously fed back to the route planning system. This feedback loop enables the system to detect when the current route is no longer valid and triggers automatic route adjustments. The feedback from sensor fusion algorithms provides real-time information about environmental changes, which is then used to modify the route accordingly.
2Productivity
If the robot stops to avoid obstacles, then collisions are prevented, but navigation efficiency and productivity decrease
Solution Approach 1:
The patent applies preliminary action by proactively planning alternative routes before collisions occur. Instead of reacting by stopping when an obstacle is detected, the system uses predictive algorithms to anticipate potential collisions and pre-calculates alternative paths. The route planning system continuously evaluates the current route's validity and prepares alternative poses in advance, allowing smooth transitions without stopping the robot.
Solution Approach 2:
The system dynamically adjusts the route in real-time to maintain navigation efficiency. When obstacles are detected, the route is dynamically modified by inserting new poses and adjusting the path sequence, allowing the robot to flow around obstacles rather than stopping. This dynamic approach maintains continuous motion while ensuring collision avoidance through real-time path recalculation.
3Reliability
If complex route adjustments are made in real-time, then collision avoidance improves, but computational resources and processing time increase
Solution Approach 1:
The patent applies segmentation by dividing the route into discrete poses that can be independently evaluated and adjusted. Instead of recalculating the entire route when an obstacle is detected, the system segments the path into individual poses and only modifies the affected segment. This segmentation allows for localized adjustments, reducing the overall computational burden while maintaining collision avoidance reliability.
Solution Approach 2:
The patent implements local quality by applying computational resources selectively to the portions of the route that are affected by obstacles. Rather than performing global route recalculation, the system focuses computational efforts on the local area where environmental changes occur. The force field adjustments and pose modifications are concentrated in the affected regions, optimizing computational resource usage while ensuring reliable collision avoidance in critical areas.
Data Source
AI summary
Systems and methods for dynamic route planning in autonomous navigation are disclosed. In some exemplary implementations, a robot can have one or more sensors configured to collect data about an environment including detected points on one or more objects in the environment. The robot can then plan a route in the environment, where the route can comprise one or more route poses. The route poses can include a footprint indicative at least in part of a pose, size, and shape of the robot along the route. Each route pose can have a plurality of points therein. Based on forces exerted on the points of each route pose by other route poses, objects in the environment, and others, each route pose can reposition. Based at least in part on interpolation performed on the route poses (some of which may be repositioned), the robot can dynamically route.