Forklift Speed Limiting From Ground Condition Sensing
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Solution Overview
Problem
Existing lifting and handling vehicles, such as forklifts and telehandlers, face challenges in managing sudden changes in speed and acceleration, tool movements, and ground artifacts, which can cause damage to fragile or unstable loads, particularly when operating on uneven terrain, and existing solutions often excessively limit performance for such loads.
Innovation Solution
A lifting or handling vehicle equipped with IMUs, cameras, and Machine Learning models to estimate maximum speed and acceleration in real-time, considering internal and external factors, and adjust performance based on load fragility and ground conditions using behavioral limitation units.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If speed limits are imposed based on ground conditions, then load safety is improved, but vehicle productivity deteriorates
Solution Approach 1:
The system dynamically adjusts speed limits based on real-time detection of ground conditions (potholes, bumps, uneven terrain) and vehicle state (acceleration, position). The speed limit is not fixed but varies continuously according to actual operating conditions, allowing the vehicle to maintain safety while maximizing productivity on each specific terrain segment
Solution Approach 2:
The system uses feedback from sensors (cameras, LIDAR, accelerometers) to continuously monitor ground conditions and vehicle response. This feedback loop allows the control system to adjust speed limits in real-time based on actual detected conditions, ensuring safety while avoiding unnecessary restrictions that would reduce productivity
2Stability of the object's composition
If performance is limited to prevent sudden speed changes, then load stability is improved, but workability deteriorates
Solution Approach 1:
The system continuously monitors vehicle acceleration and position through sensors and compares actual movement against predicted motion based on detected ground conditions. This feedback mechanism allows the system to distinguish between necessary acceleration for efficient operation and excessive acceleration that would destabilize loads, adjusting speed limits accordingly
Solution Approach 2:
The system changes the parameter of acceptable acceleration based on detected ground conditions and load characteristics. On smooth terrain, higher acceleration rates are permitted, while on uneven terrain or when fragile loads are detected, acceleration limits are reduced. This dynamic parameter adjustment maintains load stability without unnecessarily limiting workability
3Reliability
If speed restrictions are applied universally, then safety is improved, but adaptability deteriorates
Solution Approach 1:
The system implements dynamic speed restrictions that adapt to specific ground conditions rather than applying universal fixed limits. Speed limits are adjusted in real-time based on detected potholes, bumps, uneven terrain, or smooth surfaces, allowing the vehicle to maintain safety while adapting its performance characteristics to match the specific operating environment
Solution Approach 2:
The system applies different speed restrictions to different local conditions rather than uniformly across all operating scenarios. Each detected ground condition (potholes, bumps, uneven terrain) triggers specific localized speed adjustments, allowing the vehicle to maintain high adaptability by tailoring speed limits to the immediate local environment rather than applying blanket restrictions
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 the vehicle to operate safely and efficiently by dynamically adjusting speed and acceleration based on real-time ground conditions and load stability, avoiding excessive performance limitations while protecting fragile loads.
Implementation Method 1
detecting vibrations/oscillations of the vehicle (1), in particular corresponding to displacement speed and depending on the ground conditions
Implementation Method 2
a Machine Learning, ML, model embedded in one of said control units and configured to estimate ground conditions in response to signals detected by the IMU and/or the cameras and/or the odometry unit
Implementation Method 3
a behavioral limitation unit embedded in one of said control units and configured to estimate a maximum speed and acceleration in response to the estimated ground conditions
Data Source
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AI summary
A lifting or handling vehicle (1), in particular a forklift or a telehandler or an articulated loader or an aerial working platform, the vehicle (1) comprising: - at least one attachment or tool (10); - at least one Inertial Measurement Unit, IMU (3) and/or an odometry unit (6) configured to determine speed of the vehicle (1) and/or one or more cameras (5) arranged on board of the vehicle (1) and configured to acquire images and/or videos of areas around the vehicle (1); - one or more control units (2); - a Machine Learning, ML, model (7) embedded in one of the control units (2) and configured to estimate ground conditions in response to signals detected by the IMU (3) and/or the cameras (5) and/or the odometry unit (6); - a behavioral limitation unit (9) embedded in one of the control units (2) and configured to estimate a maximum speed and acceleration in response to the estimated ground conditions.