Cooperative Transportation of Aload Using Nonholonomic Mobile Robots

Loh, Chia Choon; Traechtler, Ansgar

doi:10.1016/j.proeng.2012.07.255

Cited by 15 publications

(6 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, no mechanisms for a dynamic allocation of the role are contemplated. Similar studies in which a pre-selected leader manages the motion trajectory of the object and the coordination of actions is achieved through the physical interaction with the object are presented in (Pereira et al, 2002;Loh and Traechtler, 2012). Hichri et al (2016) propose a control algorithm in which an external server globally communicates with the robots to perform the transport task.…”

Section: The Grasping Strategiesmentioning

confidence: 99%

Cooperative Object Transport in Multi-Robot Systems: A Review of the State-of-the-Art

Tuci¹,

Alkilabi²,

Akanyeti³

2018

Front. Robot. AI

181

View full text Add to dashboard Cite

In recent years, there has been a growing interest in designing multi-robot systems (hereafter MRSs) to provide cost effective, fault-tolerant and reliable solutions to a variety of automated applications. Here, we review recent advancements in MRSs specifically designed for cooperative object transport, which requires the members of MRSs to coordinate their actions to transport objects from a starting position to a final destination. To achieve cooperative object transport, a wide range of transport, coordination and control strategies have been proposed. Our goal is to provide a comprehensive summary for this relatively heterogeneous and fast-growing body of scientific literature. While distilling the information, we purposefully avoid using hierarchical dichotomies, which have been traditionally used in the field of MRSs. Instead, we employ a coarse-grain approach by classifying each study based on the transport strategy used; pushing-only, grasping and caging. We identify key design constraints that may be shared among these studies despite considerable differences in their design methods. In the end, we discuss several open challenges and possible directions for future work to improve the performance of the current MRSs. Overall, we hope to increasethe visibility and accessibility of the excellent studies in the field and provide a framework that helps the reader to navigate through them more effectively.

show abstract

Section: The Grasping Strategiesmentioning

confidence: 99%

Cooperative Object Transport in Multi-Robot Systems: A Review of the State-of-the-Art

Tuci¹,

Alkilabi²,

Akanyeti³

2018

Front. Robot. AI

181

View full text Add to dashboard Cite

show abstract

“…Yamashita et al 1998;Donald et al 2000;Cheng et al 2009); (3) placing the object on top of the robots (e.g. Tang et al 2004;Stouten and Graaf 2004;Loh and Traechtler 2012); (4) using robots with manipulators, or some sort of gripping devices (e.g. Ahmadabadi and Nakano 2001;Tanner et al 2003).…”

Section: Object Transportation By Teams Of Mobile Robotsmentioning

confidence: 99%

Attractor dynamics approach to joint transportation by autonomous robots: theory, implementation and validation on the factory floor

et al. 2018

View full text Add to dashboard Cite

This paper shows how non-linear attractor dynamics can be used to control teams of two autonomous mobile robots that coordinate their motion in order to transport large payloads in unknown environments, which might change over time and may include narrow passages, corners and sharp U-turns. Each robot generates its collision-free motion online as the sensed information changes. The control architecture for each robot is formalized as a non-linear dynamical system, where by design attractor states, i.e. asymptotically stable states, dominate and evolve over time. Implementation details are provided, and it is further shown that odometry or calibration errors are of no significance. Results demonstrate flexible and stable behavior in different circumstances: when the payload is of different sizes; when the layout of the environment changes from one run to another; when the environment is dynamic-e.g. following moving targets and avoiding moving obstacles; and when abrupt disturbances challenge team behavior during the execution of the joint transportation task.

show abstract

“…These include control methods for multiple mobile robots with compliant mechanisms between an object and the robots, e.g., couplers consisting of active prismatic links and passive rotary joints [8], mechanical sliders attached to follower robots [12], two passive-joint manipulators [1], two-joint arms with passive prismatic joints [36] [37], slideable and rotatable mechanical supports [18]; a control algorithm for two mobile robots, one of which is a leader robot and the other of which behaves as a caster robot [11]; and a control method for multiple mobile robots in formation, in which an object is assumed to be a virtual leader robot and the robots are followers [38].…”

Section: Introductionmentioning

confidence: 99%

“…Cooperative transportation systems in these control methods [8] [12] [11] [36] [1] [38] [18] [37] consist of multiple unicycle-type vehicles, which are differentially driven wheeled mobile robots. Whereas a differentially driven wheeled mobile robot can change its orientation without moving, a car-like vehicle must move in order to change its orientation, i.e., control of a car-like vehicle is more complex than that of a differentially driven wheeled mobile robot.…”

Section: Introductionmentioning

confidence: 99%

Control of two manipulation points of a cooperative transportation system with two car-like vehicles following parametric curve paths

Yamaguchi

Nishijima

Kawakami

2015

Robotics and Autonomous Systems

View full text Add to dashboard Cite

Cooperative Transportation of Aload Using Nonholonomic Mobile Robots

Cited by 15 publications

References 11 publications

Cooperative Object Transport in Multi-Robot Systems: A Review of the State-of-the-Art

Cooperative Object Transport in Multi-Robot Systems: A Review of the State-of-the-Art

Attractor dynamics approach to joint transportation by autonomous robots: theory, implementation and validation on the factory floor

Control of two manipulation points of a cooperative transportation system with two car-like vehicles following parametric curve paths

Contact Info

Product

Resources

About