Placing objects with multiple mobile robots-mutual help using intention inference

Sugie, Hiroshi; Inagaki, Y.; Ono, Shigeru; Aisu, Hideyuki; Unemi, Tatsuo

doi:10.1109/robot.1995.525583

Cited by 34 publications

(13 citation statements)

References 3 publications

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“…This paper provides a novel approach to handling boxshifting as a multi-objective optimization problem, and offers Pareto-optimal solutions in real time by utilizing the power of optimization of the NSGA-II program. The approach to the solution for the problem is unique and is different from the classical behaviour based [9] and perceptual cues based [5] multi-robot box-pushing problems. The merit of the work lies in online optimization of the cost functions, with an ultimate objective to minimize the traversal time of the box, and energy consumption by the robots using NSGA-II program.…”

Section: Computer Simulations and Experimental Resultsmentioning

confidence: 99%

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Rotation and translation selective Pareto optimal solution to the box-pushing problem by mobile robots using NSGA-II

Chakraborty

Konar

Nagar

et al. 2009

2009 IEEE Congress on Evolutionary Computation

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The paper proposes a novel formulation of the classical box-pushing problem by mobile robots as a multiobjective optimization problem, and presents Pareto optimal solution to the problem using Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed method adopts local planning scheme, and allows both turning and translation of the box in the robots' workspace in order to minimize the consumption of both energy and time. The planning scheme introduced here determines the magnitude of the forces applied by two mobile robots at specific location on the box in order to align and translate it along the time-and energy-optimal trajectory in each distinct step of motion of the box. The merit of the proposed work lies in autonomous selection of translation distance and other important parameters of the robot motion model using NSGA-II. The suggested scheme, to the best of the authors' knowledge, is a first successful realization of a communication-free, centralized cooperation between two robots used in box shifting problem satisfying both time and energy minimization objectives simultaneously, presuming no additional user-defined constraint on the selection of linear distance traversal.

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Section: Computer Simulations and Experimental Resultsmentioning

confidence: 99%

“…5(a)-5(c). The effective solution indicates the chromosome with minimum normalized product of time and energy, as given in expression (9).…”

Section: Computer Simulations and Experimental Resultsmentioning

confidence: 99%

Rotation and translation selective Pareto optimal solution to the box-pushing problem by mobile robots using NSGA-II

Chakraborty

Konar

Nagar

et al. 2009

2009 IEEE Congress on Evolutionary Computation

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“…Lozano-Perez [16] proposed a task-level (in contrast with motion-level) planning system for picking and placing objects on a table. Sugie et al [17] used rule-based planning in order to push objects on a table surface. There are some recent works using symbolic reasoning engines to plan complex manipulations for human activities, such as setting a dinner table (e.g.…”

Section: Related Workmentioning

confidence: 99%

Hallucinating Humans for Learning Robotic Placement of Objects

Jiang

Saxena

2013

Springer Tracts in Advanced Robotics

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Abstract. While a significant body of work has been done on grasping objects, there is little prior work on placing and arranging objects in the environment. In this work, we consider placing multiple objects in complex placing areas, where neither the object nor the placing area may have been seen by the robot before. Specifically, the placements should not only be stable, but should also follow human usage preferences. We present learning and inference algorithms that consider these aspects in placing. In detail, given a set of 3D scenes containing objects, our method, based on Dirichlet process mixture models, samples human poses in each scene and learns how objects relate to those human poses. Then given a new room, our algorithm is able to select meaningful human poses and use them to determine where to place new objects. We evaluate our approach on a variety of scenes in simulation, as well as on robotic experiments.

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“…To coordinate the robots' actions, robots are specifically arranged [4], [12], [14], [15], control is synchronized [12], relative positions are known [4], [14], explicit communication is used [12], [14], or individuals tasks are generated by a designated leader agent [13], [15]. Only few systems considered more than two robots, pushing a wide box simultaneously [16]- [19].…”

Section: ) Transport By Pushing or Cagingmentioning

confidence: 99%

Transport of an object by six pre-attached robots interacting via physical links

Groß

Mondada

Dorigo

Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006.

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Abstract-This paper addresses the cooperative transport of a heavy object by a group of mobile robots. We present a system in which group members lacking knowledge about the position of the transport target exploit physical interactions with other members of the group that have such knowledge. This is the first such system to achieve a performance superior to that of a passive caster. The system is fully decentralized and the information flow between the robots is limited to physical interactions. The robots have no knowledge about their relative positions. A comprehensive experimental study with up to six physical robots confirms the effectiveness, reliability, and robustness of the system. Finally, the system is examined in rough terrain conditions.

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Placing objects with multiple mobile robots-mutual help using intention inference

Cited by 34 publications

References 3 publications

Rotation and translation selective Pareto optimal solution to the box-pushing problem by mobile robots using NSGA-II

Rotation and translation selective Pareto optimal solution to the box-pushing problem by mobile robots using NSGA-II

Hallucinating Humans for Learning Robotic Placement of Objects

Transport of an object by six pre-attached robots interacting via physical links

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