Object manipulation in cluttered environments remains an open hard problem. In cluttered environments, grasping objects often fails for various reasons. This paper proposes a novel task and motion planning scheme to grasp objects obstructed by other objects in cluttered environments. Task and motion planning (TAMP) aims to generate a sequence of task-level actions where its feasibility is verified in the motion space. The proposed scheme contains an open-loop consisting of three distinct phases: 1) Generation of a task-level skeleton plan with pose references, 2) Instantiation of pose references by motion-level search, and 3) Re-planning task based on the updated state description. By conducting experiments with simulated robots, we show the high efficiency of our scheme.

Abstract
 1. 서 론
 2. 관련 연구
  2.1 작업 계획 생성
  2.2 모션 계획 생성
  2.3 작업-모션 계획의 연계
 3. 작업-모션 계획의 연계
  3.1 연계 알고리즘
  3.2 참조 기반의 작업 계획 생성
  3.3 포즈 생성
  3.4 재계획
 4. 구현 및 실험
  4.1 구현
  4.2 실험
 5. 결 론
 References

• 이석준(Computer Science, Kyonggi University) | Seokjun Lee Corresponding author
• 김인철(Computer Science, Kyonggi University) | Incheol Kim