Efficient, High-Quality Stack Rearrangement

Han, Shuai D.; Stiffler, Nicholas M.; Bekris, Kostas E.; Yu, Jingjin

doi:10.1109/lra.2018.2800116

Cited by 20 publications

(16 citation statements)

References 42 publications

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“…A more efficient algorithm that avoids backtracking builds a directed acyclic dependency graph that indicates which object is on the way of which other object, and the objects are then manipulated in the topological order of the dependency graph [3]. Tabletop rearrangement with overhand grasps was also formulated as a TSP problem and an algorithm that minimizes the total distance traveled by the end-effector was proposed [4], [5]. Rearrangement planning has also been used in robotic assembly of discrete architectural structures [20].…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, most proposed algorithms content with finding feasible plans [1]- [3]. The few efficient and optimal algorithms that have been proposed require additional constraints, such as having a clear buffer zone for intermediate placement of objects [4], [5]. Moreover, most of these works use only pick-and-place actions and do not take advantage of nonprehensile actions, such as pushing Fig.…”

Section: Introductionmentioning

confidence: 99%

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Object Rearrangement with Nested Nonprehensile Manipulation Actions

Song

Boularias

2019

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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This paper considers the problem of rearrangement planning, i.e finding a sequence of manipulation actions that displace multiple objects from an initial configuration to a given goal configuration. Rearrangement is a critical skill for robots so that they can effectively operate in confined spaces that contain clutter. Examples of tasks that require rearrangement include packing objects inside a bin, wherein objects need to lay according to a predefined pattern. In tight bins, collision-free grasps are often unavailable. Nonprehensile actions, such as pushing and sliding, are preferred because they can be performed using minimalistic end-effectors that can easily be inserted in the bin. Rearrangement with nonprehensile actions is a challenging problem as it requires reasoning about object interactions in a combinatorially large configuration space of multiple objects. This work revisits several existing rearrangement planning techniques and introduces a new one that exploits nested nonprehensile actions by pushing several similar objects simultaneously along the same path, which removes the need to rearrange each object individually. Experiments in simulation and using a real Kuka robotic arm show the ability of the proposed approach to solve difficult rearrangement tasks while reducing the length of the end-effector's trajectories.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Object Rearrangement with Nested Nonprehensile Manipulation Actions

Song

Boularias

2019

2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…While a few can handle nonmonotone plans [54], [55]; these studies do not allow stacking either. Recently, Han et al [56] study rearrangement of objects in stack-like containers (by pushes and pops); these problems do not require stability checks.…”

Section: Related Workmentioning

confidence: 99%

A Formal Framework for Robot Construction Problems: A Hybrid Planning Approach

Ahmad,

Erdem,

Patoglu

2019

Preprint

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We study robot construction problems where multiple autonomous robots rearrange stacks of prefabricated blocks to build stable structures. These problems are challenging due to ramifications of actions, true concurrency, and requirements of supportedness of blocks by other blocks and stability of the structure at all times. We propose a formal hybrid planning framework to solve a wide range of robot construction problems, based on Answer Set Programming. This framework not only decides for a stable final configuration of the structure, but also computes the order of manipulation tasks for multiple autonomous robots to build the structure from an initial configuration, while simultaneously ensuring the stability, supportedness and other desired properties of the partial construction at each step of the plan. We prove the soundness and completeness of our formal method with respect to these properties. We introduce a set of challenging robot construction benchmark instances, including bridge building and stack overhanging scenarios, discuss the usefulness of our framework over these instances, and demonstrate the applicability of our method using a bimanual Baxter robot.

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“…We develop an efficient task and motion planning algorithm which is resilient to motion planning failures. The algorithm aims to minimize the number of pick-and-place actions which often determines the efficiency of MAMO solvers [7], [8]. We begin from considering a fully known environment.…”

Section: Introductionmentioning

confidence: 99%

Fast and resilient manipulation planning for target retrieval in clutter

Nam

Lee

Cheong

et al. 2020

Preprint

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This paper presents a task and motion planning (TAMP) framework for a robotic manipulator in order to retrieve a target object from clutter. We consider a configuration of objects in a confined space with a high density so no collision-free path to the target exists. The robot must relocate some objects to retrieve the target without collisions. For fast completion of object rearrangement, the robot aims to optimize the number of pick-and-place actions which often determines the efficiency of a TAMP framework.We propose a task planner incorporating motion planning to generate executable plans which aims to minimize the number of pick-and-place actions. In addition to fully known and static environments, our method can deal with uncertain and dynamic situations incurred by occluded views. Our method is shown to reduce the number of pick-and-place actions compared to baseline methods (e.g., at least 28.0% of reduction in a known static environment with 20 objects).

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Efficient, High-Quality Stack Rearrangement

Cited by 20 publications

References 42 publications

Object Rearrangement with Nested Nonprehensile Manipulation Actions

Object Rearrangement with Nested Nonprehensile Manipulation Actions

A Formal Framework for Robot Construction Problems: A Hybrid Planning Approach

Fast and resilient manipulation planning for target retrieval in clutter

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