A Framework for Optimal Grasp Contact Planning

Hang, Kaiyu; Stork, Johannes A.; Pollard, Nancy S.; Kragić, Danica

doi:10.1109/lra.2017.2651381

Cited by 32 publications

(21 citation statements)

References 28 publications

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“…Then, we performed the regrasp task planning by searching the shortest path between the start and end poses of the object (Wan and Harada, 2017; Calandra et al , 2018). Similar graph-based methods can be found in Hang et al (2016), Cruciani et al (2018); Hang et al (2017).…”

Section: Related Workmentioning

confidence: 78%

Planning to repose long and heavy objects considering a combination of regrasp and constrained drooping

Raessa

Wan

Harada

2021

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Purpose This paper aims to present a hierarchical motion planner for planning the manipulation motion to repose long and heavy objects considering external support surfaces. Design/methodology/approach The planner includes a task-level layer and a motion-level layer. This paper formulates the manipulation planning problem at the task level by considering grasp poses as nodes and object poses for edges. This paper considers regrasping and constrained in-hand slip (drooping) during building graphs and find mixed regrasping and drooping sequences by searching the graph. The generated sequences autonomously divide the object weight between the arm and the support surface and avoid configuration obstacles. Cartesian planning is used at the robot motion level to generate motions between adjacent critical grasp poses of the sequence found by the task-level layer. Findings Various experiments are carried out to examine the performance of the proposed planner. The results show improved capability of robot arms to manipulate long and heavy objects using the proposed planner. Originality/value The authors’ contribution is that they initially develop a graph-based planning system that reasons both in-hand and regrasp manipulation motion considering external supports. On one hand, the planner integrates regrasping and drooping to realize in-hand manipulation with external support. On the other hand, it switches states by releasing and regrasping objects when the object is in stably placed. The search graphs' nodes could be retrieved from remote cloud servers that provide a large amount of pre-annotated data to implement cyber intelligence.

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Section: Related Workmentioning

confidence: 78%

Planning to repose long and heavy objects considering a combination of regrasp and constrained drooping

Raessa

Wan

Harada

2021

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“…In [19], a framework for the fingertip grasp synthesis and in-hand grasp adaptation was presented. Hang et al [20] formulated optimal grasping as a path finding problem and introduced the concept of super-contact. Zheng [21] computed the best grasp by finding contact location in a discrete point set based on combinatorial search.…”

Section: Related Workmentioning

confidence: 99%

A novel object slicing-based grasp planner for unknown 3D objects

Ansary

Deb

2021

Intel Serv Robotics

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Robotic grasp planning has been one of the active areas of research in robotics but still remains a challenging problem for arbitrary objects even in completely known environments. Most previously developed algorithms had focused on precision/fingertip type of grasps, failing to solve the problem even for fully actuated hands/grippers during enveloping/adaptive/wrapping/power type of grasps, where each finger makes contact with an object at several points. Kinematic closed-form solutions are not possible for such an articulated finger, which simultaneously reaches several given goal points. This paper presents a framework for computing the best grasp for robotic hands/grippers, based on a novel object slicing method. The proposed method quickly finds contacts using an object slicing technique and uses a grasp quality measure to find the best grasp from a pool of pre-grasps. The pool of pre-grasps is generated by dividing the objects into parts and organizing them in a decomposition tree structure, where the parts are approximated by simple box primitives. To validate the proposed method, the developed grasp planner has been implemented on an industrial Motoman robot and a two-finger gripper. Further, the results have been compared with the state-of-the-art in grasp planning to evaluate the performance of the proposed grasp planner. As compared to other existing approaches, the proposed approach has several advantages to offer. It can handle objects with complex shapes and sizes. Most importantly, it works on both point clouds taken using a depth sensor and polygonal mesh models. It takes into account hand constraints and generates feasible grasps for both adaptive/enveloping and fingertip type of grasps. KeywordsGrasp planner • Spatial search trees • Grasp quality metric • Underactuated robotic hand/gripper B Sainul Islam Ansary

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“…In order to perform an assembly task using robotic manipulator, the grasp planning is of key importance. Finding a stable grasp for objects with arbitrary shape is an active field of research [22][23][24][25], and as mentioned Grasp-RRT tries to find a grasp in a trial-and-error based way. In general, a grasp is deemed stable or feasible considering only the robot hand (or gripper) and the object, but the environment is not considered.…”

Section: Feasible Grasps For An Assembly Taskmentioning

confidence: 99%

Integrated Motion Planning for Assembly Task with Part Manipulation Using Re-Grasping

Ali

Lee

2020

Applied Sciences

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This paper presents an integrated planner based on rapidly exploring random tree (RRT) for an assembly task with possible re-grasping. Given multiple grasp poses for the part to assemble, the planner chooses candidate grasp poses considering the environment (including the partially finished assembly) in addition to the initial and final poses of the part. Orientation graph search based re-grasping approach is proposed for part manipulation which is needed when there is no feasible grasp solution for a part between its initial and final poses. Orientation graph search helps finding a series of the intermediate poses of the part needed between its initial and final poses so that robot can grasp and assemble it without interfering the pre-assembled parts. Then while extending the tree, the algorithm tries to connect the tree to a robot configuration with a chosen candidate grasp pose. Also, since the task space undergoes changes at each step of the assembly task, a node or edge in the tree can become in collision during the assembly of later parts, making the node in collision and its descendant nodes disconnected from the whole tree. To handle this, Two stage extended RRT strategy is proposed. The disconnected parts of the main tree are put into forest, and attempts are made to re-connect the tree in the forest to main tree while extending the main tree, thus making it possible to use the disconnected part again. The algorithm is implemented in Linux based system using C++. The proposed algorithm is demonstrated experimentally using UR5e robot manipulator by assembling the soma puzzle pieces in different 3D formations.

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A Framework for Optimal Grasp Contact Planning

Cited by 32 publications

References 28 publications

Planning to repose long and heavy objects considering a combination of regrasp and constrained drooping

Planning to repose long and heavy objects considering a combination of regrasp and constrained drooping

A novel object slicing-based grasp planner for unknown 3D objects

Integrated Motion Planning for Assembly Task with Part Manipulation Using Re-Grasping

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