Composite Control Element for Adaptive Robotic Platforms
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Solution Overview
Problem
Existing robotic control methods are costly and require human operators, with programming needing frequent updates for changes in robot models or environments, and remote control is inadequate for rapid dynamic changes, such as unexpected obstacles.
Innovation Solution
A method and apparatus for generating a composite control element based on a sequence of control actions, allowing a robotic platform to execute tasks with fewer user activations, using a learning process that adjusts parameters based on performance measures and sensory context, enabling autonomous operation and adaptive control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If programming is used to control robotic devices, then the robot can perform desired functionality, but changes in robot model or environment require frequent programming updates which increases cost and complexity
Solution Approach 1:
The robotic device performs self-training by autonomously collecting sensory data and adjusting its own control parameters through iterative learning processes, eliminating the need for external programmers to update code when models or environments change
Solution Approach 2:
The system performs preliminary training during dedicated training phases where the robot learns to associate sensory inputs with desired outputs before actual operation, creating a library of learned responses that can be applied without reprogramming when encountering similar situations
2Reliability
If remote control is used to operate robotic devices, then human operators can control the robot, but user experience and agility are inadequate when dynamics change rapidly such as unexpected obstacles
Solution Approach 1:
The robotic device continuously receives feedback from sensory inputs during operation and uses this feedback to autonomously adjust its control signals in real-time, enabling rapid response to unexpected obstacles without requiring operator intervention
Solution Approach 2:
The control system transitions from static pre-programmed responses to dynamic adaptive control where control parameters are continuously adjusted based on real-time sensory feedback, allowing the robot to adapt its behavior to rapidly changing environmental conditions
3Productivity
If multiple control actions are required to execute a task, then the robot can perform the task step-by-step, but frequent user activations reduce operational efficiency
Solution Approach 1:
The system merges multiple sequential control actions into a single composite control element that encapsulates an entire task sequence, allowing the robot to execute complex tasks with a single user activation rather than requiring multiple separate commands
Data Source
AI summary
A robot may be trained by a user guiding the robot along target trajectory using a control signal. A robot may comprise an adaptive controller. The controller may be configured to generate control commands based on the user guidance, sensory input and a performance measure. A user may interface to the robot via an adaptively configured remote controller. The remote controller may comprise a mobile device, configured by the user in accordance with phenotype and/or operational configuration of the robot. The remote controller may detect changes in the robot phenotype and/or operational configuration. The remote controller may comprise multiple control elements configured to activate respective portions of the robot platform. Based on training, the remote controller may configure composite controls configured based two or more of control elements. Activation of a composite control may enable the robot to perform a task.