Robot Conflict Avoidance Using Perception-Uncertainty Route Switching
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Solution Overview
Problem
Existing autonomy systems for robots are limited in extensibility as they typically focus on a narrow mission set, lacking comprehensive solutions for conflict detection and avoidance during missions, especially in dynamic environments with varying uncertainty levels.
Innovation Solution
A system and method that monitor the state of a robot and its environment, generating a local route based on perceived objects and uncertainty thresholds, allowing the robot to transition between global and local routes dynamically to manage conflict detection and avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the robot follows a global route in a dynamic environment, then the robot can maintain efficient travel, but the robot may encounter objects with high perception uncertainty leading to conflicts
Solution Approach 1:
The patent segments the navigation system into global route planning and local route generation components. The global route provides overall travel efficiency while the local route handles immediate conflict detection and avoidance in regions with high perception uncertainty, allowing both productivity and reliability to be optimized simultaneously.
Solution Approach 2:
The system dynamically switches between global and local routes based on real-time perception uncertainty. When uncertainty exceeds a threshold, the robot transitions from the global route to a generated local route, and returns to the global route when uncertainty decreases, enabling adaptive response to changing environmental conditions.
2Reliability
If the robot generates a local route to avoid objects with high uncertainty, then conflict avoidance capability is improved, but the robot deviates from the optimal global route reducing travel efficiency
Solution Approach 1:
The system dynamically adjusts the route based on perception uncertainty thresholds. The robot maintains the global route when uncertainty is low (preserving efficiency) and switches to local routes only when necessary (improving safety), thereby resolving the contradiction between reliability and productivity.
Solution Approach 2:
The system changes the routing parameter (global vs. local route) based on the uncertainty parameter. By monitoring perception uncertainty and comparing it to a threshold, the system selectively applies different routing strategies to optimize both conflict avoidance and travel efficiency.
3Measurement precision
If the robot monitors perception uncertainty continuously, then conflict detection accuracy is improved, but the system complexity and computational load increase
Solution Approach 1:
The system implements feedback by continuously monitoring perception uncertainty and using this information to control route selection. The uncertainty measurement feeds back to the routing decision, enabling accurate conflict detection while maintaining manageable system complexity through a clear feedback loop.
Solution Approach 2:
The system focuses computational resources on monitoring the critical parameter of perception uncertainty rather than all possible environmental parameters. This selective parameter monitoring improves detection accuracy while controlling system complexity by concentrating on the most relevant uncertainty measures.
Data Source
AI summary
A method is provided for detecting and avoiding conflict during a mission of a robot that includes a global route of travel. The method includes monitoring a state of the robot and a state of an environment of the robot as the robot travels the global route. The method includes generating a local route of travel through a region of the environment that includes the robot, the region having a size and shape that are set based on a type of the robot and the state of the robot when the local route is generated. A measure of uncertainty in the perception of objects in the region is monitored based on the state of the environment. And the robot is caused to maintain the global route or transition to the local route based on a comparison of the measure of uncertainty and an uncertainty threshold.