为视障场景设计更平滑稳定的轨迹生成方法
Trajectory Generation with Endpoint Regulation and Momentum-Aware Dynamics for Visually Impaired Scenarios
- 通过端点约束与动量感知动力学，提升轨迹段间一致性
- 加速度峰值降低，抖动减少，终点分布更稳定
- 适合低速动态环境下的无障碍导航系统应用
针对视障人士在结构化、低速动态环境中的轨迹生成需求，传统基于急动度的启发式采样方法在频繁重生成时易出现终端行为不稳定和状态不连续问题。本文提出一种融合端点约束与动量感知动力学的轨迹生成方法：端点约束用于稳定每段轨迹的终端状态，动量感知动力学则规范连续轨迹段间的速度与加速度演化过程。实验表明，相比基线规划器，本方法显著降低了加速度峰值与急动度水平，减少了分布离散度，实现了更平滑的速度与加速度曲线，终点分布更加稳定，且不可行轨迹候选更少。
原文摘要 · Abstract (English)
Trajectory generation for visually impaired scenarios requires smooth and temporally consistent state in structured, low-speed dynamic environments. However, traditional jerk-based heuristic trajectory sampling with independent segment generation and conventional smoothness penalties often lead to unstable terminal behavior and state discontinuities under frequent regenerating. This paper proposes a trajectory generation approach that integrates endpoint regulation to stabilize terminal states within each segment and momentum-aware dynamics to regularize the evolution of velocity and acceleration for segment consistency. Endpoint regulation is incorporated into trajectory sampling to stabilize terminal behavior, while a momentum-aware dynamics enforces consistent velocity and acceleration evolution across consecutive trajectory segments. Experimental results demonstrate reduced acceleration peaks and lower jerk levels with decreased dispersion, smoother velocity and acceleration profiles, more stable endpoint distributions, and fewer infeasible trajectory candidates compared with a baseline planner.
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