Distributed Robot Supervision With Failure Detection and Task Reassignment
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Solution Overview
Problem
Centralized control systems for robotic tasks are inadequate in low connectivity environments, as they rely on network connectivity and can be disrupted by adversarial behaviors and implicit data issues, leading to inefficient task allocation and failure detection.
Innovation Solution
A distributed supervision system where robots can assume supervisor roles, exchange messages to assign and monitor tasks, and reassign tasks upon failure, using motivation scores and alive signaling to ensure reliable task completion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If centralized control systems are used to manage robotic tasks, then task allocation can be coordinated, but the system fails in low connectivity environments and cannot detect robot failures reliably
Solution Approach 1:
The centralized control system is segmented into distributed supervisor robots that independently manage task allocation. Each supervisor robot can autonomously receive tasks, allocate them to worker robots, and detect failures without relying on a central controller, enabling operation in low connectivity environments while maintaining reliable task completion.
Solution Approach 2:
Alive signaling messages serve as intermediaries between supervisor and worker robots to verify operational status. These explicit signaling messages enable reliable failure detection in distributed architecture, replacing the implicit data reliance of previous systems and ensuring tasks are reassigned when robots fail.
2Adaptability or versatility
If distributed control without centralized supervision is used, then environmental adaptability improves, but task allocation becomes uncoordinated and failures go undetected
Solution Approach 1:
The fleet is segmented into specialized roles: supervisor robots that coordinate task allocation and worker robots that execute tasks. This segmentation provides structured coordination in distributed architecture, preventing chaotic task assignment while maintaining environmental adaptability through decentralized operation.
Solution Approach 2:
Supervisor robots send alive signaling messages to worker robots and receive acknowledgments, creating a feedback loop that verifies operational status. This feedback mechanism ensures coordinated task allocation and reliable failure detection, preventing uncoordinated behavior in distributed systems.
3Loss of energy
If implicit data is used to verify task performance, then communication overhead is reduced, but failure detection becomes unreliable and tasks may be assigned to failed robots
Solution Approach 1:
Alive signaling messages are exchanged preliminarily and periodically to verify robot operational status before and during task execution. This preliminary verification ensures reliable failure detection without excessive communication, as messages are sent at strategic intervals rather than continuously.
Solution Approach 2:
Explicit alive signaling messages serve as intermediaries to verify operational status, replacing implicit data reliance. These dedicated signaling messages provide reliable failure detection while maintaining efficient communication by focusing exchanges on critical status verification rather than continuous data transmission.
4Extent of automation
If robots use motivational behaviors to allocate tasks, then autonomous task distribution is achieved, but adversarial and arbitrary behaviors disrupt system operation
Solution Approach 1:
Supervisor robots act as intermediaries between task sources and worker robots, mediating the task allocation process. This intermediary layer filters and validates task assignments, preventing adversarial and arbitrary behaviors from disrupting the system while maintaining autonomous distributed operation.
Solution Approach 2:
The supervisor-worker acknowledgment feedback loop provides verification that task allocations are properly executed. This feedback mechanism detects and corrects arbitrary behaviors by confirming task completion status, ensuring system stability while preserving autonomous task distribution capabilities.
Data Source
AI summary
Embodiments provide systems, method, and computer-readable storage media for performing robotic tasks in a distributed and coordinated manner. A fleet of robots may use a sequence of messages to appoint supervisors for a set of tasks, where the supervisor robots are responsible for ensuring that their supervised tasks are completed by other robots of the fleet. The supervisors may solicit requests from other robots to perform available tasks and select a robot to perform an available task. Once a robot is appointed, the supervisor and the worker may use messaging sequences to monitor the status of the task and participating robots (e.g., the supervisor and the worker). The monitoring may enable the supervisor to detect a failed worker and enable other robots to detect a failed supervisor. When failed robots are detected, the robot(s) detecting the failure may initiate operations to take over the role(s) of the failed robots to ensure operation of the fleet of robots continues in a smooth manner and the tasks are completed efficiently.