Manipulator Motion Planning for Part Pickup and Transport Operations From a Moving Base

Thakar, Shantanu; Rajendran, P.; Kabir, Ariyan M.; Gupta, Satyandra K.

doi:10.1109/tase.2020.3020050

Cited by 37 publications

(15 citation statements)

References 63 publications

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“…We use the mobile manipulator in a decoupled approach, where the mobile manipulator firstly stops at the planned position and then performs the picking. A few researchers used mobile manipulators in a coupled approach [7], where the mobile manipulator picks and transports a target object while the base is moving. However, picking from a moving base is sensitive to the base positioning uncertainty and is difficult in real-world implementation.…”

Section: B Compared To Existing Researchmentioning

confidence: 99%

“…There is an increasing demand on robots which are able to flexibly perform tasks in the human environment [1] (such as opening doors [2] and fetch a cup of coffee [3]) and industrial production (e.g., inspection and sealant tasks in aerospace industry [4], robotic painting [5], robotic machining [6], and part pickup and transport operations in warehouses [7]). A mobile manipulator, combining a mobile base and a manipulator, is able to perform a variety of tasks in separate locations.…”

Section: Introductionmentioning

confidence: 99%

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Planning a Minimum Sequence of Positions for Picking Parts From Multiple Trays Using a Mobile Manipulator

Xu¹,

Domae

Ueshiba

et al. 2021

IEEE Access

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Mobile manipulators are able to operate in a large workspace, and have the potential to replace human workers to perform a sequence of pick-and-place tasks at separate locations. Many existing works optimize the base position or manipulator configuration for a single manipulation task, however, very few of them consider a sequence of tasks. In this paper, we present a planner that plans a minimum sequence of base positions for a mobile manipulator to robustly collect objects stored in multiple trays. We use inverse kinematics to determine the base region where a mobile manipulator can grasp the target objects stored in a tray, and move the mobile manipulator to the intersections of base regions to reduce the operation time for moving the base. We ensure robustness by only considering the intersection whose radius of the inscribed circle is larger than the base positioning error. Then the minimization of the number of base positions is formulated as a 0-1 knapsack problem. Besides, considering different object placements in the tray, we analyze feasible policies for dynamically updating the base sequence based on either the remaining objects or the target objects to be picked. In the experiment, we examine our planner on various scenarios, including different object placements: (1) Regularly placed toy objects; (2) Randomly placed industrial parts; and different implementation policies: (1) Apply globally static base positions; (2) Dynamically update the base positions. The experiment results show that the time for moving the base decreases by 11.22 seconds (29.37%) to 17.26 seconds (36.77%) by reducing one base movement, and demonstrate the feasibility and potential of the proposed method.INDEX TERMS Mobile manipulation, manufacturing automation, part-supply tasks, pick-and-place, tasklevel planning.

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Section: B Compared To Existing Researchmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Planning a Minimum Sequence of Positions for Picking Parts From Multiple Trays Using a Mobile Manipulator

Xu¹,

Domae

Ueshiba

et al. 2021

IEEE Access

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“…Regardless of where the manipulator is mounted, a mobile base or a fixed base, the optimization of base position shares many common criteria, such as manipulability and time-optimality of the trajectory. Thakar et al [30] considered the manipulator motion planning problem for a mobile manipulator to pick and transport a target object, where the picking is performed while the base is moving. They considered accounting for the pose estimation of the target object in [31], however, picking from a moving base is still relatively sensitive to the base position uncertainty and is not robust in real world implementation.…”

Section: Related Workmentioning

confidence: 99%

Planning a Sequence of Base Positions for a Mobile Manipulator to Perform Multiple Pick-and-Place Tasks

Xu¹,

Domae²,

Ueshiba³

et al. 2020

Preprint

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In this paper, we present a planner that plans a sequence of base positions for a mobile manipulator to efficiently and robustly collect objects stored in distinct trays. We achieve high efficiency by exploring the common areas where a mobile manipulator can grasp objects stored in multiple trays simultaneously and move the mobile manipulator to the common areas to reduce the time needed for moving the mobile base. We ensure robustness by optimizing the base position with the best clearance to positioning uncertainty so that a mobile manipulator can complete the task even if there is a certain deviation from the planned base positions. Besides, considering different styles of object placement in the tray, we analyze feasible schemes for dynamically updating the base positions based on either the remaining objects or the target objects to be picked in one round of the tasks. In the experiment part, we examine our planner on various scenarios, including different object placement: (1) Regularly placed toy objects; (2) Randomly placed industrial parts; and different schemes for online execution: (1) Apply globally static base positions; (2) Dynamically update the base positions. The experiment results demonstrate the efficiency, robustness and feasibility of the proposed method.Note to Practitioners-The presented project uses mobile manipulators to fetch and supply parts in an automotive assembly factory. Mechanical parts at these sites are usually regularly or randomly placed in supply trays. The project develops methods to explore robust mobile base positions where the objects with different placement styles and from different trays can be reached by a mobile manipulator. The mobile manipulators could perform efficient and high-quality pick-and-place operations by navigating to the explored positions. The developed methods also discuss the dynamic updates the base positions following picking process to further increase system robustness. The presented project is expected to shed light on the deployment of mobile manipulators to collect parts at large manufacturing factories.

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“…Finishing (Bhatt et al, 2019; Kabir et al, 2016, 2018c), painting (Chen et al, 2016), inspection (Yau and Menq, 1995), fiber placement (Malhan et al, 2019a,b, 2018, 2020; Shembekar et al, 2018; Shirinzadeh et al, 2007), sheet forming and handling (Li and Ceglarek, 2002), transportation (Colombo et al, 2019; Kabir et al, 2020; Thakar et al, 2018, 2019a, 2020a,b), grasping (Kumbla et al, 2017, 2018; Thakar et al, 2019b), wire harnessing (Hermansson et al, 2013; Shah and Shah, 2016), machine tending (Al-Hussaini et al, 2020; Annem et al, 2019), and 3D printing (Bhatt et al, 2018) are some of the operations where relative motion of objects can be encoded as path constraints. These path constraints or the motion of the objects can be generated using traditional motion planners (Elber and Cohen, 1994; Kuffner and LaValle, 2000).…”

Section: Introductionmentioning

confidence: 99%

Generation of synchronized configuration space trajectories with workspace path constraints for an ensemble of robots

Kabir

Thakar

Malhan

et al. 2021

The International Journal of Robotics Research

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We present an approach to generate path-constrained synchronous motion for the coupled ensemble of robots. In this article, we refer to serial-link manipulators and mobile bases as robots. We assume that the relative motion constraints among the objects in the environment are given. We represent the motion constraints as path constraints and pose the problem of path-constrained synchronous trajectory generation as a non-linear optimization problem. Our approach generates configuration space trajectories for the robots to manipulate the objects such that the given motion constraints among the objects are satisfied. We present a method that formulates the problem as a discrete parameter optimization problem and solves it using successive constraint refinement techniques. The method adaptively selects the parametric representation of the configuration variables for a given scenario. It also generates an approximate solution as the starting point for the successive constraint refinement stages to reduce the computation time. We discuss in detail why successive constraint refinement strategies are useful for solving this class of problems. We demonstrate the effectiveness of the proposed method on challenging test cases in simulation and physical environments with high-degree-of-freedom robotic systems.

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Manipulator Motion Planning for Part Pickup and Transport Operations From a Moving Base

Cited by 37 publications

References 63 publications

Planning a Minimum Sequence of Positions for Picking Parts From Multiple Trays Using a Mobile Manipulator

Planning a Minimum Sequence of Positions for Picking Parts From Multiple Trays Using a Mobile Manipulator

Planning a Sequence of Base Positions for a Mobile Manipulator to Perform Multiple Pick-and-Place Tasks

Generation of synchronized configuration space trajectories with workspace path constraints for an ensemble of robots

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