3D Safe-Zone Motion Planning for Human-Robot Workspaces
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Solution Overview
Problem
Existing industrial machinery safety systems struggle to efficiently integrate human movement into motion planning while adhering to stringent safety standards, often leading to suboptimal operation or excessive guarding that constrains workspace use.
Innovation Solution
A system utilizing multiple 3D sensors to create a dynamic 3D representation of the workspace, identifying safe zones, and generating constrained motion plans that avoid unsafe areas, adjusting in real-time to ensure safe and efficient operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional guarding approaches (cages, light curtains) are used to ensure human safety, then safety is improved, but workspace utilization and machinery efficiency deteriorate due to excessive guarding constraints
Solution Approach 1:
The system dynamically adjusts the robot's operational state (stop, slow down, continue) based on real-time detection of human presence and classification of workspace zones. Instead of static guarding that prevents all interaction, the system adapts its safety responses to current conditions, allowing productive workspace utilization while maintaining safety through dynamic control adjustments.
Solution Approach 2:
The workspace is divided into different zones (e.g., safe zones, monitoring zones, exclusion zones) with different safety requirements and levels of restriction. This allows the system to apply appropriate safety measures locally rather than uniformly across the entire workspace, enabling productive activities in safe zones while maintaining strict safety controls in hazardous areas.
2Difficulty of detecting and measuring
If 2D LIDAR or optical sensors are used for intrusion detection, then detection capability is improved, but detection accuracy and safety effectiveness worsen due to inability to distinguish depth and occluded objects
Solution Approach 1:
The system transitions from 2D detection planes to 3D volumetric detection by incorporating depth information through multiple sensors and ray-tracing algorithms. This dimensional enhancement allows the system to accurately distinguish objects at different depths, detect occluded objects, and precisely locate intrusions in three-dimensional space, thereby improving both detection capability and measurement precision.
3Reliability
If safety standards require stopping machinery at detected intrusions, then human safety is improved, but machinery efficiency and productivity worsen due to frequent interruptions
Solution Approach 1:
The system changes the control parameters (speed, position, operational mode) based on the detected zone and risk level rather than always stopping completely. For minor intrusions in less critical zones, the system may adjust speed or position parameters to maintain safety while continuing operation, thereby improving productivity without compromising safety.
Solution Approach 2:
The system continuously monitors the workspace and provides real-time feedback to adjust machinery operation. This closed-loop control allows the system to respond appropriately to each detection event, making informed decisions about whether to stop, slow down, or continue operation based on the current safety assessment, thus optimizing both safety and productivity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables safe and efficient operation of machinery by dynamically adapting to changing workspace conditions, maximizing machinery use while ensuring human safety through real-time sensor monitoring and motion planning.
Implementation Method 1
3D time-of-flight cameras
Implementation Method 2
3D LIDAR
Implementation Method 3
2D LIDAR sensors that use active optical sensing to detect the minimum distance to an obstacle
Data Source
AI summary
A method of safely operating machinery in a workspace includes recording images of a portion of a workspace. The method also includes generating a three-dimensional (3D) representation of the portion of the workspace based on the recorded images, where the 3D representation includes one or more volumes that correspond to the portion of the workspace. Additionally, the method includes identifying one or more of the volumes as being either occupied or unoccupied. Further, the method includes mapping one or more safe zones based on the one or more identified volumes, where the safe zones correspond to one or more regions within the portion of the workspace for safe operation of machinery.