Autonomous Machine M2M Capability Sharing for Obstacle Avoidance
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Solution Overview
Problem
Autonomous machines face obstacles in path planning and communication with remote servers in unfavorable network conditions, leading to failed obstacle avoidance maneuvers and incomplete task completion.
Innovation Solution
A machine-to-machine (M2M) communication mesh enables autonomous machines to share capabilities and solutions among a team, allowing one machine to assist another in resolving issues by sharing sensors, visual range, or resources to complete tasks autonomously.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous machines rely on remote servers for obstacle avoidance and path planning, then task completion can be achieved in favorable network conditions, but task completion fails in unfavorable network conditions
Solution Approach 1:
The patent merges the autonomous machine's local capabilities with remote server capabilities by establishing a hybrid system where the machine autonomously performs basic obstacle avoidance while selectively communicating with the remote server for complex path planning when network conditions permit. This combining approach ensures task completion reliability by not depending solely on remote server connectivity.
Solution Approach 2:
The autonomous machine implements self-service by autonomously detecting obstacles and executing avoidance maneuvers using its own sensors and processors, without requiring constant remote server intervention. The machine independently manages its navigation tasks while using the remote server supplementsively for enhanced path planning when network conditions are favorable.
2Productivity
If autonomous machines perform obstacle avoidance maneuvers independently, then task completion can proceed in weak network conditions, but the machine lacks access to advanced path planning capabilities
Solution Approach 1:
The system dynamically adjusts its level of autonomy based on network conditions. When network connectivity is strong, the machine adopts a more collaborative mode, utilizing advanced path planning capabilities from the remote server. When network connectivity is weak or unavailable, the machine transitions to independent autonomous operation, maintaining basic obstacle avoidance capabilities. This dynamic adaptation ensures continuous task completion while optimizing path planning based on available resources.
Data Source
AI summary
Described is a method for utilizing machine to machine communications to facilitate capability sharing includes determining a first machine out of a group of machines has encountered an issue, that cannot be resolved, where the group of machines are connected via a machine to machine (M2M) communication mesh. The method also includes determining a solution to the issue encountered by the first machine while performing an assigned task The method also includes determining, based on structured messages provided by a management hub, a second machine from the group of machines can provide the first solution to the issue encountered by the first machine. The method also includes providing to the first machine a first sharable capability of the second machine, where the first sharable capability resolves the issue encountered by the first machine.