Robot Foot Swing Height Control From Terrain Height Maps
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Solution Overview
Problem
Legged robotic devices face challenges in efficiently navigating varied terrain, as they often require high-stepping to avoid obstacles, which increases energy consumption and may not always be necessary, and existing sensor systems can be uncertain about the actual path of the foot relative to the environment.
Innovation Solution
A control system that processes sensor data into a topographical map to identify potential obstacles and adjust the swing height of the robotic device's feet based on the highest point within a scan patch of cells encompassing the step path, allowing the robot to lift its feet only high enough to clear obstacles while minimizing energy expenditure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robotic device lifts its feet high to avoid obstacles, then the robot can successfully navigate terrain, but energy consumption increases
Solution Approach 1:
The system dynamically changes the swing height parameter based on terrain analysis. Instead of maintaining a fixed high swing height, the controller adjusts the parameter to match the actual obstacle height, reducing energy consumption when high clearance is not needed while maintaining navigation reliability when obstacles are present
Solution Approach 2:
The swing height is made dynamic rather than static. The system continuously senses terrain features and adjusts the leg swing height in real-time, transitioning between low-energy normal stepping and high-energy obstacle clearing only when necessary, thereby resolving the contradiction between reliable navigation and energy efficiency
2Measurement precision
If the robotic device uses sensor data to map terrain, then navigation accuracy improves, but system complexity increases
Solution Approach 1:
The terrain mapping process is segmented into discrete cells in a grid representation. Each cell contains simplified height information rather than continuous data, reducing processing complexity while maintaining sufficient accuracy for determining swing height. The environment is divided into manageable units that can be processed independently
Solution Approach 2:
Instead of processing complex raw sensor data directly, the system creates a simplified copy or model of the terrain in the form of a height map with discrete cells. This abstract representation captures essential terrain features needed for navigation while dramatically reducing the computational complexity of the control system
Data Source
AI summary
An example implementation includes (i) receiving sensor data that indicates topographical features of an environment in which a robotic device is operating, (ii) processing the sensor data into a topographical map that includes a two-dimensional matrix of discrete cells, the discrete cells indicating sample heights of respective portions of the environment, (iii) determining, for a first foot of the robotic device, a first step path extending from a first lift-off location to a first touch-down location, (iv) identifying, within the topographical map, a first scan patch of cells that encompass the first step path, (v) determining a first high point among the first scan patch of cells; and (vi) during the first step, directing the robotic device to lift the first foot to a first swing height that is higher than the determined first high point.