MIVG: Mode-Isolated Velocity-Guide Algorithm for Quadratic Optimization-Based Obstacle Avoidance

Dynamic obstacle avoidance is a challenging problem in robotic control, with many algorithms developed to balance efficiency and real-time performance. Existing resolved-rate motion control (RRMC) methods formulate obstacle avoidance as a quadratic programming (QP) problem. However, the lack of directional guidance for obstacle avoidance and frequent constraint conflicts often lead to execution failures. In this work, we propose the Mode-Isolated Velocity-Guide (MIVG) algorithm that deploys a dual-mode isolation strategy combined with a Velocity-Guide Potential Field (VGPF). This novel approach separates obstacle avoidance from target-driven tasks while providing velocity-based directional guidance. Simulations on a 7-degree-of-freedom Franka Emika Panda robot demonstrate that our approach significantly enhances task success rates while maintaining real-time feasibility, achieving an increase in execution success rates of 35. 0% ~ 52. 0% compared to the baseline RRMC strategy (NEO). Additionally, we analyze the impact of key parameters through simulations, further validating the effectiveness of the proposed algorithm in dynamic environments.

Authors

• Hangyu Lin
• Xiaoqi Chen
• Songyin Cai
• Xiangrui Lin
• Kunpeng Wu

Keywords

• Analytical models
• Heuristic algorithms
• Dynamics
• Real-time systems
• Quadratic programming
• Collision avoidance
• Intelligent robots
• Obstacle Avoidance
• Motor Control
• Dynamic Environment
• Real-time Performance
• Robot Control
• Quadratic Programming Problem
• Increased Success Rate
• Dynamic Obstacles
• Computational Efficiency
• Minimum Distance
• Local Point
• Transformation Matrix
• Task Execution
• Equality Constraints
• Path Planning
• Jacobian Matrix
• Local Velocity
• Slack Variables
• Dynamic Adjustment
• Baseline Algorithms
• Artificial Potential Field
• Joint Velocity
• Dynamic Scenarios
• Matrix Of Points
• Adjacent Joints
• Mode Transition
• Efficient Path
• Average Success Rate