Efficient Multi-Robot Kinodynamic Motion Planning with db-CBS
The author presents db-CBS, an efficient motion planner for multi-robot systems that considers dynamics and control bounds. The approach combines CBS and db-A* to find near-optimal solutions quickly.
iDb-RRT: Sampling-based Kinodynamic Motion Planning with Motion Primitives and Trajectory Optimization
Combining motion primitives, bounded discontinuity, and trajectory optimization in iDb-RRT for efficient kinodynamic motion planning.
Efficient Motion Planning for Mobile Robots with Non-Trivial Dynamics using Learned Controllers and Roadmaps with Gaps
This work proposes a decoupled strategy that first trains a goal-conditioned controller offline in an empty environment to deal with the robot's dynamics, and then constructs a "Roadmap with Gaps" to approximately learn how to solve planning queries in a target environment using the learned controller. The roadmap guidance is integrated with an asymptotically optimal tree sampling-based planner to achieve improved computational efficiency for motion planning.
Differentiable Motion Manifold Primitives (DMMP) for Fast and Adaptive Kinodynamic Motion Planning of Robot Arms
This paper introduces a novel method using Differentiable Motion Manifold Primitives (DMMP) to achieve fast and adaptive kinodynamic motion planning for robots, enabling them to efficiently plan complex motions while adhering to dynamic constraints.
高速かつ適応的な運動計画のための軌道多様体最適化：7自由度ロボットアームによる動的投擲タスクのケーススタディ
高次元な運動計画問題を効率的に解決するために、タスクに関連する軌道の低次元多様体を学習し、その多様体内で最適化を行うことで、高速かつ適応的な運動生成を可能にする新しい手法を提案する。
고차원 운동 계획 문제 해결을 위한 궤적 매니폴드 최적화: 7-자유도 로봇 팔의 동적 던지기 과제를 중심으로
고차원 동적 환경에서 빠른 운동 계획을 위해서는 전체 궤적 공간 대신 작업 관련 동작으로 구성된 저차원 궤적 매니폴드를 식별하고 그 안에서 해를 검색하는 것이 효과적이다.
基於軌跡流形優化的快速自適應運動規劃
本文提出了一種基於軌跡流形優化的快速自適應運動規劃方法，通過離線學習低維流形並線上搜索最優軌跡，顯著提高了機器人在動態環境中的規劃速度和任務成功率。