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

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 increase the visibility and accessibility of the excellent studies in the field and provide a framework that helps the reader to navigate through them more effectivelypublishersversionPeer reviewe

Hierarchical Decentralized LQR Control for Formation-Keeping of Cooperative Mobile Robots in Material Transport Tasks

This study provides a formation-keeping method based on consensus for mobile robots used in cooperative transport applications that prevents accidental damage to the objects being carried. The algorithm can be used to move both rigid and elastic materials, where the desired formation geometry is predefined. The cooperative mobile robots must maintain formation even when encountering unknown obstacles, which are detected using each robot's on-board sensors. Local actions would then be taken by the robot to avoid collision. However, the obstacles may not be detected by other robots in the formation due to line-of-sight or range limitations. Without sufficient communication or coordination between robots, local collision avoidance protocols may lead to the loss of formation geometry. This problem is most notable when the object being transported is deformable, which reduces the physical force interaction between robots when compared to rigid materials. Thus, a decentralized, hierarchical LQR control scheme is proposed that guarantees formation-keeping despite local collision avoidance actions, for both rigid and elastic objects. Representing the cooperative robot formation using multi-agent system framework, graph Laplacian potential and Lyapunov stability analysis are used to guarantee tracking performance and consensus. The effectiveness and scalability of the proposed method are illustrated by computer simulations of line (2 robots) and quadrilateral (4 robots) formations. Different communication topologies are evaluated and provide insights into the minimum bandwidth required to maintain formation consensus

Virtual Coordination in Collective Object Manipulation

Inspired by nature, swarm robotics aims to increase system robustness while utilizing simple agents. In this work, we present a novel approach to achieve decentralized coordination of forces during collective manipulation tasks resulting in a highly scalable, versatile, and robust solution. In this approach, each robot involved in the collective object manipulation task relies on the behavior of a cooperative ``virtual teammate\u27 in a fully decentralized architecture, regardless of the size and configuration of the real team. By regulating their actions with their corresponding virtual counterparts, robots achieve continuous pose control of the manipulated object, while eliminating the need for inter-agent communication or a leader-follower architecture. To experimentally study the scalability, versatility, and robustness of the proposed collective object manipulation algorithm, a new swarm agent, Δρ is introduced which is able to apply linear forces in any planar direction. Efficiency and effectiveness of the proposed decentralized algorithm are investigated by quantitative performance metrics of settling time, steady-state error, path efficiency, and object velocity profiles in comparison with a force-optimal centralized version that requires complete information. Employing impedance control during manipulation of an object provides a mean to control its dynamic interactions with the environment. The proposed decentralized algorithm is extended to achieve a desired multi-dimensional impedance behavior of the object during a collective manipulation without inter-agent communication. The proposed algorithm extension is built upon the concept of ``virtual coordination\u27 which demands every agent to locally coordinate with one virtual teammate. Since the real population of the team is unknown to the agents, the resultant force applied to the manipulated object would be directly scaled with the team population. Although this scaling effect proves useful during position control of the object, it leads to a deviation from the desired dynamic response when employed in an impedance control scheme. To minimize such deviations, a gradient descent algorithm is implemented to determine a scaling parameter defined on the control action. The simulation results of a multi-robot system with different populations and formations verify the effectiveness of the proposed method in both generating the desired impedance response and estimating the population of the group. Eventually, as two case studies, the introduced algorithm is used in robotic collective manipulation and human- assistance scenarios. Simulation and experimental results indicate that the proposed decentralized communication- free algorithm successfully performs collective manipulation in all tested scenarios, and matches the performance of the centralized controller for increasing number of agents, demonstrating its utility in communication- limited systems, remote environments, and access-limited objects

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

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 dynamice.g. following moving targets and avoiding moving obstacles; and when abrupt disturbances challenge team behavior during the execution of the joint transportation task.- This work was supported by FCT-Fundacao para a Ciencia e Tecnologia within the scope of the Project PEst-UID/CEC/00319/2013 and by the Ph.D. Grants SFRH/BD/38885/2007 and SFRH/BPD/71874/2010, as well as funding from FP6-IST2 EU-IP Project JAST (Proj. Nr. 003747). We would like to thank the anonymous reviewers, whose comments have contributed to improve the paper

Object Manipulation using a Multirobot Cluster with Force Sensing

This research explored object manipulation using multiple robots by developing a control system utilizing force sensing. Multirobot solutions provide advantages of redundancy, greater coverage, fault-tolerance, distributed sensing and actuation, and reconfigurability. In object manipulation, a variety of solutions have been explored with different robot types and numbers, control strategies, sensors, etc. This research involved the integration of force sensing with a centralized position control method of two robots (cluster control) and building it into an object level controller. This controller commands the robots to push the object based on the measured interaction forces between them while maintaining proper formation with respect to each other and the object. To test this controller, force sensor plates were attached to the front of the Pioneer 3-AT robots. The object is a long, thin, rectangular prism made of cardboard, filled with paper for weight. An Ultra Wideband system was used to track the positions and headings of the robots and object. Force sensing was integrated into the position cluster controller by decoupling robot commands, derived from position and force control loops. The result was a successful pair of experiments demonstrating controlled transportation of the object, validating the control architecture. The robots pushed the object to follow linear and circular trajectories. This research is an initial step toward a hybrid force/position control architecture with cluster control for object transportation by a multirobot system

Occlusion-based cooperative transport with a swarm of miniature mobile robots

This paper proposes a strategy for transporting a large object to a goal using a large number of mobile robots that are significantly smaller than the object. The robots only push the object at positions where the direct line of sight to the goal is occluded by the object. This strategy is fully decentralized and requires neither explicit communication nor specific manipulation mechanisms. We prove that it can transport any convex object in a planar environment. We implement this strategy on the e-puck robotic platform and present systematic experiments with a group of 20 e-pucks transporting three objects of different shapes. The objects were successfully transported to the goal in 43 out of 45 trials. When using a mobile goal, teleoperated by a human, the object could be navigated through an environment with obstacles. We also tested the strategy in a 3-D environment using physics-based computer simulation. Due to its simplicity, the transport strategy is particularly suited for implementation on microscale robotic systems