Sensor-Based Robot Motion Planning Within Workspace Footprints
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Solution Overview
Problem
Current robotics planning methods require extensive manual programming, which is time-consuming and error-prone, and fail to account for real-time physical constraints of workcells and robot movements, leading to inefficiencies and potential collisions.
Innovation Solution
A system that generates and modifies motion plans in real-time using sensor data to optimize robot trajectories and paths within a predefined workspace footprint, ensuring safe operation and collision avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual programming is used to dictate robotic movements, then the robot can perform skills with precise control, but the programming process becomes tedious, time-consuming, and error-prone
Solution Approach 1:
The system enables robots to automatically generate their own motion plans by utilizing sensor data and predefined workspace footprints. Instead of requiring manual programming for each movement, the robot autonomously plans its trajectory between sensor-based skills, reducing programming time while maintaining movement precision through constraint-based path generation
Solution Approach 2:
The system changes the approach from fixed manual programming to dynamic parameter-based planning. By using sensor measurements and real-time data to adjust motion parameters, the system generates appropriate trajectories automatically, eliminating the need for tedious manual programming while preserving precise control through constraint enforcement
2Productivity
If a motion schedule is manually generated for one workcell, then the robot can operate efficiently in that specific environment, but the schedule cannot be used for other workcells with different physical properties
Solution Approach 1:
The system creates a universal motion planning framework that can adapt to different workcells through predefined workspace footprints. Instead of requiring separate manual schedules for each workcell, the same planning system generates appropriate trajectories by incorporating sensor data and physical constraints specific to each environment, enabling one system to serve multiple workcells efficiently
Solution Approach 2:
The system transitions from static manual schedules to dynamic motion planning that adapts to different workcell configurations. By using sensor measurements and real-time data, the system dynamically generates motion plans tailored to each specific workcell's physical properties, maintaining efficiency while achieving versatility across different environments
3Ease of operation
If sensor-based skills are planned in real-time, then the robot can respond to actual conditions during execution, but current systems fail to account for physical constraints of the workcell
Solution Approach 1:
The system applies local quality by defining specific workspace footprints for different regions of the workcell. These footprints encode local physical constraints and safety zones, allowing the robot to make real-time decisions within bounded spaces that guarantee collision avoidance. The local constraint information enables responsive yet safe operation without requiring global replanning
Solution Approach 2:
The system performs preliminary action by pre-defining workspace footprints and safety constraints before robot execution. These pre-established boundaries and constraints are incorporated into the real-time planning process, enabling the robot to respond dynamically to sensor data while automatically respecting physical limitations and avoiding collisions through pre-planned safe zones
4Adaptability or versatility
If the robot is allowed to move freely within the workcell, then the robot can access all necessary areas to perform skills, but other robots or objects may be interfered with or collided with
Solution Approach 1:
The system segments the workcell into distinct workspace footprints, each representing a safe operational zone for specific skills or robots. This segmentation allows each robot to move freely within its assigned footprint while the collective segmentation of all footprints prevents inter-robot collisions and interference with other objects, balancing movement freedom with safety
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for controlling robotic movements. One of the methods includes receiving, for a robot, a definition of a plurality of sensor-based skills to be executed in sequence, wherein each skill is associated with an entry point and an exit point; generating a motion plan for the robot, including: generating, for a first skill of the plurality of sensor-based skills, a first path from a first entry point of the first skill to a second point at which a sensor-based interaction of the first skill begins, and generating, for the first skill of the plurality of sensor-based skills, a second path from a third point at which the sensor-based interaction of the first skill ends to a first exit point of the first skill; and executing the motion plan for the robot.