Cooperative object transportation by multiple mobile manipulators through a hierarchical planning architecture

Hekmatfar, Taher; Masehian, Ellips; Mousavi, Seyed Javad

doi:10.1109/icrom.2014.6990952

Cited by 14 publications

(6 citation statements)

References 11 publications

(13 reference statements)

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“…Another widespread technique is that of leader-follower, where a robot determines the movement of the object and defines the behavior of the others [9][10][11][12][13]. In addition, more recent strategies make use of swarm intelligence, a variation of which is followed in this work, in which homogeneous robots are used, which are based on decentralized and collective behaviors [14]. Finally, techniques based on machine learning and artificial intelligence have also appeared, which understandably require high computing power [15].…”

Section: Related Workmentioning

confidence: 99%

Mutli-Robot Cooperative Object Transportation with Guaranteed Safety and Convergence in Planar Obstacle Cluttered Workspaces via Configuration Space Decomposition

2022

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In this work, we consider the autonomous object transportation problem employing a team of mobile manipulators within a compact planar workspace with obstacles. As the object is allowed to translate and rotate and each robot is equipped with a manipulator consisting of one or more moving links, the overall system (object and mobile manipulators) should adapt its shape in a flexible way so that it fulfills the transportation task with safety. To this end, we built a sequence of configuration space cells, each of which defines an allowable set of configurations of the object, as well as explicit intervals for each manipulator’s states. Furthermore, appropriately designed under- and over-approximations of the free configuration space are used in an innovative way to guide the configuration space’s exploration without loss of completeness. In addition, we coupled methodologies based on Reference Governors and Prescribed Performance Control with harmonic maps, in order to design a distributed control law for implementing the transitions specified by the high-level planner, which possesses guaranteed invariance and global convergence properties, thus avoiding the requirement for synchronized motion as inherently dictated by the majority of the related works. Furthermore, the proposed low-level control law does not require continuous information exchange between the robots, which rely only on measurements of the object’s configuration and their own states. Finally, a transportation scenario within a complex warehouse workspace demonstrates the proposed approach and verifies its efficiency.

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Section: Related Workmentioning

confidence: 99%

Mutli-Robot Cooperative Object Transportation with Guaranteed Safety and Convergence in Planar Obstacle Cluttered Workspaces via Configuration Space Decomposition

2022

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“…To achieve accurate part identification and the robot location, the authors use an array of radiofrequency identifiers to compute location. In Hekmatfar et al (2014), an algorithm that allows a group of KUKA youBot, to cooperate to manipulate large objects avoiding collisions, is presented. To achieve that, they implemented two interconnected planners.…”

Section: Related Workmentioning

confidence: 99%

Dynamic categorization of 3D objects for mobile service robots

Rios‐Cabrera

López-Juárez

Maldonado-Ramírez

et al. 2020

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Purpose This paper aims to present an object detection methodology to categorize 3D object models in an efficient manner. The authors propose a dynamically generated hierarchical architecture to compute very fast objects’ 3D pose for mobile service robots to grasp them. Design/methodology/approach The methodology used in this study is based on a dynamic pyramid search and fast template representation, metadata and context-free grammars. In the experiments, the authors use an omnidirectional KUKA mobile manipulator equipped with an RGBD camera, to localize objects requested by humans. The proposed architecture is based on efficient object detection and visual servoing. In the experiments, the robot successfully finds 3D poses. The present proposal is not restricted to specific robots or objects and can grow as much as needed. Findings The authors present the dynamic categorization using context-free grammars and 3D object detection, and through several experiments, the authors perform a proof of concept. The authors obtained promising results, showing that their methods can scale to more complex scenes and they can be used in future applications in real-world scenarios where mobile robot are needed in areas such as service robots or industry in general. Research limitations/implications The experiments were carried out using a mobile KUKA youBot. Scalability and more robust algorithms will improve the present proposal. In the first stage, the authors carried out an experimental validation. Practical implications The current proposal describes a scalable architecture, where more agents can be added or reprogrammed to handle more complicated tasks. Originality/value The main contribution of this study resides in the dynamic categorization scheme for fast detection of 3D objects, and the issues and experiments carried out to test the viability of the methods. Usually, state-of-the-art treats categories as rigid and make static queries to datasets. In the present approach, there are no fixed categories and they are created and combined on the fly to speed up detection.

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“…The Kuka youBot has been subject of study for motion planning of k-OMM, wherein the base orientation is particularly addressed for obstacle avoidance based on a conventional artificial potential functions, [25]. As an alternative approach, we propose passive velocity field design, [26], to address passivity for desired trajectories of the base.…”

Section: Introductionmentioning

confidence: 99%

Cooperative redundant omnidirectional mobile manipulators: Model-free decentralized integral sliding modes and passive velocity fields

Ponce-Hinestroza

Castro-Castro

Guerrero-Reyes

et al. 2016

2016 IEEE International Conference on Robotics and Automation (ICRA)

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An omnidirectional mobile manipulator (OMM) provides extended capabilities to a robotic system since it enlarges its workspace at the expense of an omnidirectional mobile base, which is nowadays a reality. When various OMM transport an object, the resultant constrained OMM dynamics is quite complex that demands effective control schemes without neglecting dominant nonlinear effects nor interaction forces. In this paper, it is proposed a decentralized cooperative control for a set of k OMMs (k-OMM) subject to homogeneous holonomic constraints imposed by the object being manipulated. A chatterless integral sliding mode force-position control guarantees exponential tracking whose implementation does not require any knowledge of dynamics. This controller is decentralized in a sense that neither dynamics nor interaction forces of the i-OMM are required for the j-controller, and it is cooperative by correcting collectively the velocity deviation due to the pushing of the other j-OMM. Each omnidirectional base provides object mobility along passive smooth velocity fields to avoid obstacles on the floor, which is synthesized as the secondary task when resolving redundancy, and the force control stabilizes internal forces to ensure object grasp, which are declared together with end-effector position, as the primary task. Simulations are discussed for two 8-DoF Kuka youBot OMM system navigating in a cluttered environment.

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Cooperative object transportation by multiple mobile manipulators through a hierarchical planning architecture

Cited by 14 publications

References 11 publications

Mutli-Robot Cooperative Object Transportation with Guaranteed Safety and Convergence in Planar Obstacle Cluttered Workspaces via Configuration Space Decomposition

Mutli-Robot Cooperative Object Transportation with Guaranteed Safety and Convergence in Planar Obstacle Cluttered Workspaces via Configuration Space Decomposition

Dynamic categorization of 3D objects for mobile service robots

Cooperative redundant omnidirectional mobile manipulators: Model-free decentralized integral sliding modes and passive velocity fields

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