Planning pick-and-place tasks with two-hand regrasping

Saut, Jean-Philippe; Gharbi, M.; Cortés, Juan; Sidobre, Daniel; Siméon, Thierry

doi:10.1109/iros.2010.5649021

Cited by 61 publications

(26 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This limits the applicable objects to simple meshes. Some other work, for example, Saut et al [14], uses surface sampling [15] and box decomposition [16] to approximate the objects. Xue et al [17] uses shape primitives proposed in [18] to approximate the objects.…”

Section: A Grasp Planningmentioning

confidence: 99%

Improving regrasp algorithms to analyze the utility of work surfaces in a workcell

Wan

Mason²,

Fukui

et al. 2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

The goal of this paper is to develop a regrasp planning algorithm general enough to perform statistical analysis with thousands of experiments and arbitrary mesh models. We focus on pick-and-place regrasp which reorients an object from one placement to another by using a sequence of pickups and place-downs. We improve the pick-and-place regrasp approach developed in 1990s and analyze its performance in robotic assembly with different work surfaces in the workcell. Our algorithm will automatically compute the stable placements of an object, find several force-closure grasps, generate a graph of regrasp actions, and search for regrasp sequences. We demonstrate the advantages of our algorithm with various mesh models and use the algorithm to evaluate the completeness, the cost and the length of regrasp sequences with different mesh models and different assembly tasks in the presence of different work surfaces. Our results show that spare work surfaces are beneficial to assembly. Tilted work surfaces are only sometimes beneficial, depending on the objects.

show abstract

Section: A Grasp Planningmentioning

confidence: 99%

Improving regrasp algorithms to analyze the utility of work surfaces in a workcell

Wan

Mason²,

Fukui

et al. 2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

View full text Add to dashboard Cite

show abstract

“…The approach allows for scenarios where a fast IK solver is not available whereas our method requires IK for our representation. In [14] the authors solve the problem of finding good grasps to use when a handoff between two arms is known to be needed. Our approach solves what this algorithm assumes, determining what handoffs are needed.…”

Section: Related Workmentioning

confidence: 99%

Planning Single-arm Manipulations with n-Arm Robots

Cohen

Phillips²,

Likhachev

2014

Robotics: Science and Systems X

View full text Add to dashboard Cite

Abstract-Many robotic systems are comprised of two or more arms. Such systems range from dual-arm household manipulators to factory floors populated with a multitude of industrial robotic arms. While the use of multiple arms increases the productivity of the system and extends dramatically its workspace, it also introduces a number of challenges. One such challenge is planning the motion of the arm(s) required to relocate an object from one location to another. This problem is challenging because it requires reasoning over which arms and in which order should manipulate the object, finding a sequence of valid handoff locations between the consecutive arms and finally choosing the grasps that allow for successful handoffs. In this paper, we show how to exploit the characteristics of this problem in order to construct a planner that can solve it effectively. We analyze our approach experimentally on a number of simulated examples ranging from a 2-arm system operating at a table to a 3-arm system working at a bar and to a 4-arm system in a factory setting.

show abstract

“…The focus of this research, however, seemed more on image processing and path planning than on arm-hand coordination for assembly tasks. Other instances of arm-hand coordinated solutions focus on pick-and-place operations and rudimentary material handling (e.g., Saut et al (2010) and Rodríguez et al (2013)). …”

Section: Arm-hand Assembly Strategiesmentioning

confidence: 99%

Multi-Robot Assembly Strategies and Metrics

2018

View full text Add to dashboard Cite

We present a survey of multi-robot assembly applications and methods and describe trends and general insights into the multi-robot assembly problem for industrial applications. We focus on fixtureless assembly strategies featuring two or more robotic systems. Such robotic systems include industrial robot arms, dexterous robotic hands, and autonomous mobile platforms, such as automated guided vehicles. In this survey, we identify the types of assemblies that are enabled by utilizing multiple robots, the algorithms that synchronize the motions of the robots to complete the assembly operations, and the metrics used to assess the quality and performance of the assemblies.

show abstract

Planning pick-and-place tasks with two-hand regrasping

Cited by 61 publications

References 32 publications

Improving regrasp algorithms to analyze the utility of work surfaces in a workcell

Improving regrasp algorithms to analyze the utility of work surfaces in a workcell

Planning Single-arm Manipulations with n-Arm Robots

Multi-Robot Assembly Strategies and Metrics

Contact Info

Product

Resources

About