Spatiotemporal Robot Control for Conflict-Free Shared Resources
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Robots in congested environments face inefficiencies due to fixed programmed movements, leading to increased collisions, deadlocks, and missed objectives, as they lack the ability to make granular adjustments to avoid conflicts and adapt to changing conditions.
Innovation Solution
A spatiotemporal controller that continuously and granularly adjusts the actuators of a robot to align with dynamic objectives and workarounds, using sensors and flexible actuator control to manage power, speed, and movement within allotted time intervals, ensuring conflict-free operation and timely completion of tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If robots operate according to fixed programmed movements, then the robot operation is simple and predictable, but the robot efficiency decreases and collisions increase in congested environments
Solution Approach 1:
The patent implements dynamic control by allowing robots to continuously adjust their movements, speeds, and trajectories in real-time based on sensor feedback about the environment and other robots. This replaces fixed programmed movements with adaptive, dynamic control that responds to changing conditions, thereby improving efficiency in congested environments while managing complexity through systematic feedback loops.
Solution Approach 2:
The system employs continuous feedback mechanisms where sensors monitor robot positions, velocities, and environmental conditions, and this information feeds back to the control system to adjust movements. This feedback loop enables robots to preemptively avoid conflicts and optimize their paths, resolving the contradiction between operational simplicity and efficiency by making control responsive rather than rigid.
2Reliability
If robots make granular adjustments to avoid conflicts, then collision avoidance improves, but the control complexity increases
Solution Approach 1:
The control system performs preliminary actions by calculating and planning conflict avoidance maneuvers in advance based on predicted trajectories of other robots. By anticipating potential collisions and preparing avoidance actions before conflicts occur, the system improves reliability without requiring complex real-time reaction mechanisms, thus managing control complexity effectively.
Solution Approach 2:
Continuous sensor feedback about robot positions and velocities enables the control system to detect potential conflicts early and adjust movements preemptively. This feedback-driven approach improves collision avoidance by maintaining awareness of the operational environment, while the systematic nature of the feedback processing keeps control complexity manageable.
3Reliability
If robots interrupt movements to avoid conflicts, then safety improves, but productivity decreases due to cascading interruptions
Solution Approach 1:
The patent implements continuous useful action by enabling robots to maintain their primary tasks while simultaneously making small, continuous adjustments to avoid conflicts. Rather than interrupting movements entirely, the system allows robots to weave through congested environments smoothly, preserving task completion rates while ensuring safety through continuous conflict avoidance maneuvers.
Solution Approach 2:
Dynamic control enables robots to balance safety and productivity by continuously adjusting their trajectories and speeds in response to environmental conditions. This dynamic approach allows robots to maintain forward momentum and complete tasks while adaptively navigating around obstacles and other robots, avoiding the productivity loss associated with complete movement interruptions.
4Adaptability or versatility
If robots operate in congested environments with fixed movements, then device simplicity is maintained, but deadlocks and conflicts increase
Solution Approach 1:
The system achieves environmental adaptability through dynamic control that continuously adjusts robot movements based on real-time sensor data about congestion levels, other robots' positions, and environmental obstacles. This dynamic adaptation allows robots to effectively operate in varying congestion conditions without requiring fundamentally different control systems for different environments, managing complexity through a unified adaptive framework.
Solution Approach 2:
The control system implements universality by using a single adaptive control framework that handles multiple functions: path planning, collision avoidance, task completion, and environmental adaptation. This multi-functional approach enables robots to operate effectively across different congestion levels and environmental conditions without requiring separate specialized systems, thereby achieving adaptability while controlling overall system complexity.
Data Source
AI summary
A robot may include a spatiotemporal controller for controlling the kinematics or movements of the robot via continuous and/or granular adjustments to the actuators that perform the physical operations of the robot. The spatiotemporal controller may continuously and/or granularly adjust the actuators to align completion or execution of different objectives or waypoints from a spatiotemporal plan within time intervals allotted for each objective by the spatiotemporal plan. The spatiotemporal controller may also continuously and/or granularly adjust the actuators to workaround unexpected conflicts that may arise during the execution of an objective and delays that result from a workaround while still completing the objective within the allotted time interval. By completing objectives within the allotted time intervals, the spatiotemporal controller may ensure that conflicts do not arise as the robots simultaneously operate in the site using some of the same shared resource.