Robotic Mobile Manipulation System with Visual Feedback
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Solution Overview
Problem
Mobile robots face challenges in manipulating objects in dynamic environments shared with humans, due to uncertainty in object locations and navigation, which complicates pre-planning of robot and manipulator movements.
Innovation Solution
A processor-implemented method and system that acquires images while moving a manipulator relative to a task location, detects feature points, and generates motion trajectories for the robot base and manipulator to reposition and interact with objects, allowing for adaptive navigation and manipulation planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the robot base is stationary and the manipulator operates in consistent locations, then manipulation precision is improved, but mobility and adaptability to dynamic environments deteriorate
Solution Approach 1:
The system transitions from static pre-planned trajectories to dynamic real-time trajectory generation. The robot base and manipulator execute motion trajectories that are generated adaptively during operation based on current sensor data and object locations, allowing the system to maintain precision while adapting to environmental changes.
Solution Approach 2:
The system continuously acquires sensor data from the environment, detects object locations in real-time, and uses this feedback to adjust motion trajectories dynamically. This closed-loop control enables the robot to respond to changes in object positions and environmental conditions while maintaining manipulation accuracy.
2Productivity
If pre-planned motion trajectories are used, then task execution efficiency is improved, but flexibility in dynamic environments with moving objects deteriorates
Solution Approach 1:
The system generates motion trajectories dynamically during task execution rather than relying solely on pre-planned paths. This allows the robot to adapt to moving objects and environmental changes while maintaining efficient task completion through automated real-time trajectory generation.
Solution Approach 2:
The system continuously acquires sensor data, detects objects, and generates motion trajectories without interruption during task execution. This continuous operation ensures both efficiency and adaptability by maintaining uninterrupted task progress while responding to environmental changes.
3Adaptability or versatility
If the robot moves between locations to access objects, then accessibility and task coverage are improved, but navigation complexity and task planning difficulty increase
Solution Approach 1:
The system merges navigation planning and manipulation planning into a unified real-time trajectory generation process. By combining base motion and manipulator motion planning into a single integrated system that operates dynamically, the complexity of coordinating separate navigation and manipulation tasks is reduced.
Solution Approach 2:
The system replaces complex mechanical coordination and manual programming with automated sensor-based detection and algorithmic trajectory generation. This substitution reduces planning complexity by using computational methods to automatically determine optimal motions based on real-time environmental data.
Data Source
AI summary
The present approach relates to integrated planning of robot navigation and manipulator motion in performing tasks. In particular, as discussed herein sensor information, such as visual information, may be used for the robot to locate a target object when it arrives at a working location. Adjustments may be made based on this information that may include moving the robot and planning a manipulator arm motion.