Autonomous Debris Relocation Robot for Hazardous Terrain Clearing
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Solution Overview
Problem
Current human-labor powered technologies for debris clearing in hazardous environments, such as post-disaster or combat zones, pose significant risks to workers and are inefficient, with challenges including non-uniform terrain, hazardous materials, and scarce worker availability.
Innovation Solution
An autonomous object relocation robot system comprising a self-propelled vehicle with gripper assemblies, a sensor package, and a processor that uses visual, LIDAR, acoustic, and load cell data to identify and manipulate objects, enabling efficient debris clearing and path creation for rescue and recovery efforts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human-labor powered technologies are used for debris clearing, then workers can directly manipulate and remove objects, but workers are exposed to significant physical and mental hazards including live electrical wires, gas leaks, toxic chemicals, and bacterial contaminants
Solution Approach 1:
The patent replaces human-operated mechanical systems with autonomous robotic systems equipped with sensors, processors, and manipulators. The robotic system uses computer vision, LIDAR, and force sensors to detect, classify, and manipulate debris objects without human exposure to hazards. The autonomous navigation and object manipulation capabilities eliminate the need for workers to physically enter hazardous zones.
Solution Approach 2:
The robotic system acts as an intermediary between the hazardous environment and human operators. Remote operators can control or monitor the robot from safe locations, allowing debris clearing operations to proceed without direct human exposure to toxic chemicals, live wires, and other dangerous conditions.
2Productivity
If heavy machinery such as earth movers and bulldozers are used for debris clearing, then large volumes of debris can be moved quickly, but the machinery encounters non-uniform terrain, fallen trees, boulders, and mudslides that hinder advancement
Solution Approach 1:
The robotic system features dynamically adjustable manipulators and gripper assemblies that can adapt to different object sizes, shapes, and weights. The autonomous navigation system continuously adjusts the robot's path planning to navigate around obstacles such as fallen trees, boulders, and uneven terrain, providing both speed and adaptability.
Solution Approach 2:
The debris clearing task is segmented into discrete operations: detection, classification, grasping, lifting, and transport. The robotic manipulator system can selectively engage different gripper configurations and force levels based on object characteristics, allowing efficient handling of diverse debris types without requiring heavy machinery.
3Productivity
If multiple heavy vehicles are deployed for debris clearing and path creation, then more debris can be removed simultaneously, but coordinating synchronized efforts becomes challenging and resource-intensive
Solution Approach 1:
The robotic system is designed as a multi-functional platform capable of autonomous navigation, object detection, classification, grasping, lifting, and transport. This universal design allows a single robot to perform multiple tasks that would otherwise require coordinated heavy machinery, reducing overall system complexity while maintaining productivity.
Solution Approach 2:
The robotic system incorporates multiple sensors including force sensors, LIDAR, and computer vision systems that provide real-time feedback for autonomous control. This feedback mechanism enables the robot to autonomously adapt to changing conditions and coordinate with other robots or remote operators without complex communication protocols.
4Measurement precision
If manual labor is used for debris clearing in post-disaster environments, then workers can identify and prioritize specific objects for removal, but worker availability is scarce and response times are slow
Solution Approach 1:
The robotic system replaces human visual inspection and decision-making with automated computer vision and machine learning algorithms. These systems can rapidly analyze sensor data, classify objects by type and priority, and make removal decisions without fatigue or scarcity constraints, significantly reducing response time while maintaining or improving identification accuracy.
Solution Approach 2:
The autonomous robotic system can operate continuously without breaks, shifts, or availability constraints. The robot maintains continuous surveillance and debris clearing operations, eliminating the interruptions and resource constraints associated with manual labor in post-disaster environments.
Data Source
AI summary
A self-propelled device is disclosed to recognize objects, possess objects, and transport objects to a new location. A method is disclosed to use the device to transport objects in environments dangerous to humans. Other example embodiments are described and claimed.