通过正弦轨迹与速度缩放结合，实现高自由度机器人高效节能的平滑运动规划。
A Robust and Energy-Efficient Trajectory Planning Framework for High-Degree-of-Freedom Robots
- 采用正弦轨迹生成+速度缩放策略优化能量消耗
- 仿真测试显示能耗显著降低，运动平滑且轨迹精准
- 适合对精度与能效要求高的工业机器人场景
高自由度机器人的轨迹规划中，能效与运动平滑性对性能优化和机械磨损控制至关重要。本文提出一种新框架，结合正弦轨迹生成与速度缩放技术，在保证运动精度与平滑性的前提下最小化能耗。该框架在基于物理的仿真环境中进行评估，采用能耗、运动平滑性和轨迹准确性等指标。结果表明，该方法实现了显著的能耗降低与平滑过渡，验证了其在精密应用中的有效性。未来工作将聚焦于实时轨迹调整与更精确的能量模型构建。
原文摘要 · Abstract (English)
Energy efficiency and motion smoothness are essential in trajectory planning for high-degree-of-freedom robots to ensure optimal performance and reduce mechanical wear. This paper presents a novel framework integrating sinusoidal trajectory generation with velocity scaling to minimize energy consumption while maintaining motion accuracy and smoothness. The framework is evaluated using a physics-based simulation environment with metrics such as energy consumption, motion smoothness, and trajectory accuracy. Results indicate significant energy savings and smooth transitions, demonstrating the framework's effectiveness for precision-based applications. Future work includes real-time trajectory adjustments and enhanced energy models.
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