KCFRC: Kinematic Collision-Aware Foothold Reachability Criteria for Legged Locomotion
🤖 AI Summary
This work addresses the challenge of real-time collision safety verification for swing-leg trajectories in legged robots operating in complex environments, which hinders efficient and reliable foothold selection and contact planning. The authors propose the Kinematic Constraint–Collision Feasibility Reachability Criterion (KCFRC), a novel method that jointly models kinematic constraints and collision detection to establish a sufficient condition for real-time verifiable foothold reachability—thereby filling a critical gap in collision-free swing trajectory validation. By integrating geometric reachability analysis with efficient collision checking within a real-time planning framework, KCFRC enables rapid evaluation of candidate footholds: on average, it verifies 900 potential footholds for a single leg in just 2 milliseconds. This substantial acceleration of trajectory optimization significantly enhances the robot’s adaptability and robustness in confined spaces.
Application Category
📝 Abstract
Legged robots face significant challenges in navigating complex environments, as they require precise real-time decisions for foothold selection and contact planning. While existing research has explored methods to select footholds based on terrain geometry or kinematics, a critical gap remains: few existing methods efficiently validate the existence of a non-collision swing trajectory. This paper addresses this gap by introducing KCFRC, a novel approach for efficient foothold reachability analysis. We first formally define the foothold reachability problem and establish a sufficient condition for foothold reachability. Based on this condition, we develop the KCFRC algorithm, which enables robots to validate foothold reachability in real time. Our experimental results demonstrate that KCFRC achieves remarkable time efficiency, completing foothold reachability checks for a single leg across 900 potential footholds in an average of 2 ms. Furthermore, we show that KCFRC can accelerate trajectory optimization and is particularly beneficial for contact planning in confined spaces, enhancing the adaptability and robustness of legged robots in challenging environments.
Problem
Research questions and friction points this paper is trying to address.
legged locomotion
foothold selection
collision avoidance
reachability analysis
swing trajectory
Innovation
Methods, ideas, or system contributions that make the work stand out.
KCFRC
foothold reachability
collision-aware swing trajectory
legged locomotion
real-time contact planning
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