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Kunpeng Wu

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IROS Conference 2025 Conference Paper

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

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

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.

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