Biped Robot Running Gait Control on Rough Terrain
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Solution Overview
Problem
Current biped robots face challenges in achieving a stable running gait on rough terrain due to limitations in mechanical design and control strategies, particularly the ZMP stability criterion, which restricts their adaptability to complex environments.
Innovation Solution
A method utilizing a hybrid inverted pendulum model that switches between SLIP and LIP models for balance control, combined with state machine-based movement planning and trajectory control, allows for dynamic running on rough terrain by stabilizing posture and center of mass during different phases of the gait cycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If ZMP stability criterion is used for control, then balance stability is improved, but adaptability to rough terrain deteriorates
Solution Approach 1:
The patent transitions from static ZMP stability criterion to dynamic running gait control. The robot dynamically switches between walking and running gaits based on terrain conditions, with the running gait featuring an air phase where both feet are off the ground simultaneously. This dynamic approach allows the robot to maintain balance stability while adapting to rough terrain by adjusting gait parameters in real-time.
Solution Approach 2:
The control strategy changes key parameters including switching from single-support phase to double-air phase gait, adjusting foot placement coordinates, and modifying joint angle trajectories. These parameter changes enable the robot to achieve both balance stability and terrain adaptability by optimizing gait characteristics for different terrain conditions.
2Stability of the object's composition
If large foot design is adopted, then balance stability is improved, but adaptability to complex roads deteriorates
Solution Approach 1:
Instead of relying on large static foot design, the patent employs dynamic gait control where the robot coordinates leg movements and foot placement to achieve balance. The running gait with air phase allows the robot to maintain stability without requiring oversized feet, thereby improving adaptability to complex road surfaces while preserving balance capabilities.
3Speed
If running gait is adopted, then moving speed is improved, but dynamic balance control difficulty increases
Solution Approach 1:
The running gait cycle is segmented into distinct phases: left leg support phase, right leg support phase, and air phase where both legs are simultaneously off the ground. This segmentation allows the control system to manage dynamic balance by focusing on specific phases, reducing overall control complexity while achieving higher speeds.
Solution Approach 2:
The patent implements periodic switching between walking and running gaits, with each gait consisting of periodic cycles of support and air phases. This periodic structure simplifies dynamic balance control by creating predictable, repeating patterns that can be controlled through standardized trajectories and timing, enabling high-speed movement without excessive control complexity.
4Speed
If air phase duration is extended, then moving speed is improved, but joint motor performance requirements increase
Solution Approach 1:
The patent implements a partial air phase where both feet are off the ground for a limited duration, rather than extending the air phase to maximum possible length. This partial action approach achieves speed improvement while keeping joint motor performance requirements within practical limits, balancing speed enhancement with hardware feasibility.
Data Source
AI summary
The present disclosure provides a method for realizing a dynamic running gait of a biped robot on a rough terrain road, which sets a state machine for an entire running cycle to perform a balance control and movement trajectory planning of the robot in each state. At the time that the robot switches from the in-air phase into a landing phase, a SLIP model is used to control the posture balance and landing cushion; and when the robot is stable after landing, an LIP model is used to control a center of mass of the robot to a set height. An in-air phase of the robot in running is generated through movement trajectory planning and state switching of a supporting leg and a swinging leg to realize a running of the robot.