Wearable Robot Vision Control for Terrain-Aware Foot Placement
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Solution Overview
Problem
Wearable robots, such as medical robots for rehabilitation, face difficulties in navigating environments with stairs or height variations due to lack of environmental perception capabilities.
Innovation Solution
A vision control apparatus and method using an RGB-Depth camera and IMU sensor to generate a grid-type elevation map, enabling the wearable robot to perceive terrain features like flat ground, stairs, and sloped roads, and calculate optimal foot positions for navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a wearable robot is equipped with vision control technology including RGB-Depth camera and IMU sensor to perceive terrain environment, then the robot's ability to navigate various terrain (flat ground, stairs, sloped roads) is improved, but the device complexity and computational requirements increase
Solution Approach 1:
The vision control apparatus segments the terrain perception process into distinct functional modules: RGB-Depth camera for capturing depth information, IMU sensor for orientation detection, point cloud generation module, terrain type classification module, and foot position calculation module. This segmentation allows each component to perform its specific function efficiently, reducing overall system complexity while maintaining high adaptability for navigating various terrain types.
Solution Approach 2:
The vision control apparatus uses multi-functional sensors (RGB-Depth camera and IMU) that serve multiple purposes: the RGB-Depth camera captures both visual and depth information for terrain perception, while the IMU provides orientation data that complements the visual information. This multi-functionality reduces the need for separate specialized sensors, thereby managing device complexity while enhancing terrain navigation capability across diverse environments.
2Measurement precision
If the robot uses point cloud-based geometric information and grid-type elevation map for precise terrain perception, then the measurement precision of terrain features is improved, but the processing time and computational load increase
Solution Approach 1:
The system performs preliminary actions by pre-processing depth information into point cloud format and pre-calculating grid-type elevation maps before terrain navigation is required. The RGB-Depth camera continuously captures depth data and converts it to point clouds, which are then organized into elevation maps in advance. This preliminary processing reduces real-time computational load during actual navigation, maintaining high measurement precision while minimizing processing time delays.
Solution Approach 2:
The vision control apparatus dynamically adjusts its processing based on terrain complexity and robot movement state. For simple flat terrain, the system uses simplified processing with lower computational requirements, while for complex terrain like stairs or sloped roads, it activates full point cloud-based geometric information processing. This dynamic adaptation maintains high measurement precision when needed while reducing processing time during simpler navigation tasks.
Data Source
AI summary
An apparatus of a wearable robot may comprise a transceiver configured to communicate with at least one controller of the wearable robot, at least one processor, and memory. The memory may store instructions that, when executed by the at least one processor, are configured to cause the vision control apparatus to receive, from the at least one controller of the wearable robot via a receiver of the transceiver, an indicator of a current robot foot position, detect, via a depth camera of the wearable robot, a characteristic of terrain around the wearable robot, generate, based on the detected characteristic of terrain, point cloud-based geometric information associated with the terrain, determine, based on the current robot foot position and the point cloud-based geometric information, a subsequent robot foot position, and transmit, to the at least one controller of the wearable robot via a transmitter of the transceiver, the determined subsequent robot foot position.