Incorporating Motion Planning Feasibility Considerations during Task-Agent Assignment to Perform Complex Tasks Using Mobile Manipulators

Kabir, Ariyan M.; Thakar, Shantanu; Bhatt, Prahar M.; Malhan, Rishi K.; Rajendran, P.; Shah, Brual C.; Gupta, Satyandra K.

doi:10.1109/icra40945.2020.9196667

Cited by 21 publications

(7 citation statements)

References 53 publications

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“…e authors of [33] proposed a novel online planning and execution system to solve a TAMP problem as a hybrid partially observable Markov decision process (POMDP) and use past plans to constrain the structure of solutions for the current planning problem. On the other hand, both [34,35] addressed multi-agent or multi-robot TAMP problems. e authors of [34] dealt with a new problem of motion planning feasibility checking for task-agent assignment to perform complex tasks using multi-arm mobile manipulators.…”

Section: State Of Artmentioning

confidence: 99%

“…On the other hand, both [34,35] addressed multi-agent or multi-robot TAMP problems. e authors of [34] dealt with a new problem of motion planning feasibility checking for task-agent assignment to perform complex tasks using multi-arm mobile manipulators. e authors of [35] presented a multi-robot integrated task and motion planning method capable of handling sequential subtasks dependencies within multiple decomposable tasks.…”

Section: State Of Artmentioning

confidence: 99%

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Constraint Satisfaction for Motion Feasibility Checking

Lee

Kim

2021

Mathematical Problems in Engineering

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Task and motion planning (TAMP) is a key research field for robotic manipulation tasks. The goal of TAMP is to generate motion-feasible task plan automatically. Existing methods for checking motion feasibility of task plan skeletons have some limitations of semantic-free pose candidate sampling, weak search heuristics, and early value commitment. In order to overcome these limitations, we propose a novel constraint satisfaction framework for checking motion feasibility of task plan skeletons. Our framework provides (1) a semantic pose candidate sampling method, (2) novel variable and constraint ordering heuristics based on intra- and inter-action dependencies in a task plan skeleton, and (3) an efficient search strategy using constraint propagation. Based upon these techniques, our framework can improve the efficiency of motion feasibility checking for TAMP. From experiments using the humanoid robot PR2, we show that the motion feasibility checking in our framework is 1.4x to 6.0x faster than previous ones.

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Section: State Of Artmentioning

confidence: 99%

Section: State Of Artmentioning

confidence: 99%

Constraint Satisfaction for Motion Feasibility Checking

Lee

Kim

2021

Mathematical Problems in Engineering

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“…Recent efforts have formulated the ST-MR-TA problem as tree and graph-search problems [18], [19]. Both of the approaches in [18] and [19] first schedule tasks into a sequence of temporal windows and then allocate robots to these tasks.…”

Section: Related Workmentioning

confidence: 99%

An Interleaved Approach to Trait-Based Task Allocation and Scheduling

Neville¹,

Messing²,

Ravichandar³

et al. 2021

Preprint

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To realize effective heterogeneous multi-robot teams, researchers must leverage individual robots' relative strengths and coordinate their individual behaviors. Specifically, heterogeneous multi-robot systems must answer three important questions: who (task allocation), when (scheduling), and how (motion planning). While specific variants of each of these problems are known to be NP-Hard, their interdependence only exacerbates the challenges involved in solving them together. In this paper, we present a novel framework that interleaves task allocation, scheduling, and motion planning. We introduce a search-based approach for trait-based timeextended task allocation named Incremental Task Allocation Graph Search (ITAGS). In contrast to approaches that solve the three problems in sequence, ITAGS's interleaved approach enables efficient search for allocations while simultaneously satisfying scheduling constraints and accounting for the time taken to execute motion plans. To enable effective interleaving, we develop a convex combination of two search heuristics that optimizes the satisfaction of task requirements as well as the makespan of the associated schedule. We demonstrate the efficacy of ITAGS using detailed ablation studies and comparisons against two state-of-the-art algorithms in a simulated emergency response domain.

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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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Incorporating Motion Planning Feasibility Considerations during Task-Agent Assignment to Perform Complex Tasks Using Mobile Manipulators

Cited by 21 publications

References 53 publications

Constraint Satisfaction for Motion Feasibility Checking

Constraint Satisfaction for Motion Feasibility Checking

An Interleaved Approach to Trait-Based Task Allocation and Scheduling

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

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