Robotic Path Planning With Real-Time Map Updates for Coverage
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Solution Overview
Problem
Current robotic devices face inefficiencies in path planning due to preprogrammed route plans that do not adapt to real-time environmental changes, leading to increased U-turns and incomplete coverage of areas.
Innovation Solution
A path planning method that uses a topological graph represented by vertices and edges, with properties determined in real-time based on sensory input, allowing the robotic device to dynamically adjust its route plan and coverage pattern within bounded areas, and adjust in response to obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If preprogrammed route plans are used, then device complexity is reduced, but adaptability to real-time environmental changes deteriorates
Solution Approach 1:
The patent implements dynamic route planning where the robotic device continuously updates its route plan based on real-time sensor data and environmental changes. The system transitions from static preprogrammed routes to dynamic adaptive routing, allowing the device to respond to obstacles and modify its path during execution, thereby resolving the contradiction between simplicity and adaptability.
Solution Approach 2:
The system incorporates feedback mechanisms where sensor data from the environment is continuously fed back to the route planning algorithm. This feedback loop enables the system to adjust route plans in real-time based on actual environmental conditions, obstacle detections, and cleaning progress, maintaining adaptability without requiring overly complex preprogramming.
2Ease of operation
If preprogrammed route plans are used, then ease of operation is improved, but productivity deteriorates due to increased U-turns and incomplete coverage
Solution Approach 1:
The system performs preliminary actions by pre-planning routes based on initial environmental maps before execution. However, it enhances this by allowing dynamic modifications during execution, combining the benefits of preplanning (ease of operation) with real-time adaptability (productivity improvement) to reduce unnecessary U-turns and ensure complete coverage.
Solution Approach 2:
The route planning system dynamically changes parameters such as route coordinates, speed profiles, and coverage patterns based on real-time environmental feedback. This parameter adaptation allows the system to maintain ease of operation through automated planning while improving productivity by optimizing paths to minimize U-turns and maximize area coverage.
3Productivity
If the route plan is devised within a bounded area smaller than total discovered area, then productivity is improved through focused coverage, but adaptability to new areas deteriorates
Solution Approach 1:
The patent segments the working environment into multiple bounded areas or zones. The robotic device can focus on completing coverage within current bounded areas to maintain high productivity, while the system retains adaptability to discover and plan for new areas as they are detected, allowing flexible expansion of the working boundary without compromising cleaning efficiency in already-discovered regions.
Solution Approach 2:
The bounded area definition is made dynamic rather than static. The system can adjust the boundaries of the current working area based on discovery progress and cleaning priorities. This dynamic boundary management allows the device to maintain focused productivity within current bounds while adapting to incorporate new discovered areas into future route plans.
Data Source
AI summary
Provided is a method including obtaining a map of an environment of a robot; maneuvering the robot to a first location and orientation that positions the robot to sense a part of the working environment at a second location of the working environment; sensing, while the robot is at the first location, the part of the physical layout of the working environment at the second location; updating the map of the physical layout of the working environment; determining at least a part of a route plan of the robot through the working environment; and maneuvering the robot along the at least the part of the route plan.