Robotic Foot Swing Height Control for Obstacle-Clearing Steps
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Solution Overview
Problem
Legged robotic devices face challenges in efficiently navigating varied terrains due to uncertainty in step path prediction, leading to potential tripping on obstacles and increased energy consumption from unnecessary high-stepping.
Innovation Solution
A control system processes sensor data into a topographical map to identify a scan patch encompassing the step path, determines a high point within this patch, and adjusts the swing height of the robotic device's foot to clear obstacles while minimizing energy expenditure by only high-stepping as necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the robotic device uses a fixed high swing height to clear all potential obstacles, then the reliability of navigation is improved, but the energy consumption increases due to unnecessary high-stepping on flat terrain
Solution Approach 1:
The swing height is made dynamic rather than fixed. The control system continuously adjusts the swing height based on real-time terrain information from the topographical map. When obstacles are detected in the step path, the swing height increases to clear them; when terrain is flat, the swing height returns to normal, optimizing energy consumption while maintaining navigation reliability.
Solution Approach 2:
The swing height parameter is changed dynamically based on terrain conditions. The system processes sensor data to identify obstacles and adjusts the swing height parameter accordingly - increasing it when obstacles are present in the scan patch and maintaining normal values when terrain is clear, thus resolving the contradiction between reliability and energy consumption.
2Use of energy by moving object
If the robotic device uses a low swing height to minimize energy consumption, then energy efficiency is improved, but the risk of tripping on obstacles increases
Solution Approach 1:
The system performs preliminary analysis of the terrain by processing sensor data into a topographical map and identifying obstacles in the step path before executing the step. This allows the robotic device to adjust the swing height in advance to clear detected obstacles, preventing trips while avoiding unnecessary energy consumption on clear terrain.
Solution Approach 2:
The control system uses feedback from sensor data and the topographical map to continuously monitor the environment and adjust swing height accordingly. The system receives feedback about terrain features and obstacle locations, processes this information, and modifies the swing height command to maintain safe clearance over obstacles while optimizing energy efficiency.
3Measurement precision
If the robotic device processes extensive sensor data to accurately predict step paths, then the precision of obstacle avoidance is improved, but the computational complexity and processing time increase
Solution Approach 1:
The sensor data processing is segmented into focused tasks: creating a topographical map from sensor data, identifying a specific scan patch around the step path, and detecting obstacles within that patch. This segmentation allows precise obstacle detection without requiring complex processing of entire environment data, balancing precision with computational efficiency.
Solution Approach 2:
The system applies local quality by concentrating processing resources on the scan patch - a localized region around the step path - rather than uniformly processing all sensor data. This allows high precision in identifying obstacles relevant to the current step while reducing overall computational complexity by ignoring areas outside the scan patch.
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.