Robot Leg Swing Trajectory Planning for Fast Obstacle Clearance
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Solution Overview
Problem
Legged robots face challenges in navigating constrained environments efficiently while maintaining balance and avoiding obstacles, often resulting in slow and arduous movements with frequent collisions and loss of balance.
Innovation Solution
A method for planning leg swing trajectories that involves receiving initial position and velocity data, determining horizontal and vertical motion components, and selecting appropriate policies from sets of horizontal and vertical motion policies to execute a swing trajectory that ensures timely and obstacle-avoiding movement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional gait control methods are used, then the robot can maintain stability, but the navigation speed is slow and the robot frequently collides with obstacles
Solution Approach 1:
The patent segments the leg swing motion into horizontal and vertical components, allowing independent optimization of each dimension. The horizontal component controls forward progression and obstacle avoidance, while the vertical component manages ground clearance and stability. This segmentation enables faster navigation without compromising collision avoidance reliability.
Solution Approach 2:
The patent implements dynamic adjustment of swing trajectory parameters based on real-time environmental perception and gait state. The system continuously modifies horizontal and vertical motion components to adapt to changing terrain and obstacle conditions, enabling high-speed navigation while maintaining reliable obstacle avoidance through real-time dynamic control.
2Productivity
If aggressive swing trajectories are used to increase speed, then navigation efficiency improves, but the robot loses balance frequently
Solution Approach 1:
By separating horizontal and vertical motion control, the patent allows aggressive horizontal trajectories for speed while maintaining conservative vertical control for stability. The horizontal component can be optimized for rapid progression, while the vertical component ensures adequate ground clearance and balanced foot placement, resolving the contradiction between navigation efficiency and balance stability.
Solution Approach 2:
The patent dynamically adjusts swing trajectory parameters including amplitude, frequency, and phase relationship between horizontal and vertical components. By optimizing these parameters, the system achieves aggressive yet balanced motion patterns that improve navigation efficiency while maintaining balance stability through coordinated parameter adjustment.
3Reliability
If complex real-time navigation algorithms are implemented, then obstacle avoidance capability improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent segments the navigation problem into independent horizontal and vertical control sub-problems. This segmentation simplifies the computational complexity by allowing separate optimization of each dimension rather than solving a complex three-dimensional trajectory optimization problem, while maintaining reliable obstacle avoidance capability through coordinated control of both components.
Solution Approach 2:
The patent implements a dynamic control framework that adjusts swing parameters in real-time based on simplified models and heuristics rather than complex real-time optimization. This dynamic approach reduces computational complexity while maintaining reliable obstacle avoidance through adaptive parameter adjustment based on environmental feedback.
Data Source
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AI summary
A method (1700) of planning a swing trajectory (132) for a leg (12) of a robot (10) includes receiving an initial position (50) of a leg of the robot, an initial velocity (52) of the leg, a touchdown location (62), and a touchdown target time (64). The method includes determining a difference between the initial position and the touchdown location and separating the difference into a horizontal motion component and a vertical motion component. The method also includes selecting a horizontal motion policy (210) and a vertical motion policy (610) to satisfy the motion components. Each policy produces a respective trajectory as a function of the initial position, the initial velocity, the touchdown location, and the touchdown target time. The method also includes executing the selected policies to swing the leg of the robot from the initial position to the touchdown location at the touchdown target time.