Enhancing the terrain adaptability of a multirobot cooperative transportation system via novel connectors and optimized cooperative strategies

Abstract

Given limited terrain adaptability, most existing multirobot cooperative transportation systems (MRCTSs) mainly work on flat pavements, restricting their outdoor applications. The connectors’ finite deformation capability and the control strategies’ limitations are primarily responsible for this phenomenon. This study proposes a novel MRCTS based on tracked mobile robots (TMRs) to improve terrain adaptability and expand the application scenarios of MRCTSs. In structure design, we develop a novel 6-degree-of-freedom passive adaptive connector to link multiple TMRs and the transported object (the communal payload). In addition, the connector is set with sensors to measure the position and orientation of the robot with respect to the object for feedback control. In the control strategy, we present a virtual leader–physical follower collaborative paradigm. The leader robot is imaginary to describe the movement of the entire system and manage the follower robots. All the TMRs in the system act as follower robots to transport the object cooperatively. Having divided the whole control structure into the leader robot level and the follower robot level, we convert the motion control of the two kinds of robots to trajectory tracking control problems and propose a novel double closed-loop kinematics control framework. Furthermore, a control law satisfying saturation constraints is derived to ensure transportation stability. An adaptive control algorithm processes the wheelbase uncertainty of the TMR. Finally, we develop a prototype of the TMR-based MRCTS for experiments. In the trajectory tracking experiment, the developed MRCTS with the proposed control scheme can converge to the reference trajectory in the presence of initial tracking errors in a finite time. In the outdoor experiment, the proposed MRCTS consisting of four TMRs can successfully transport a payload weighing 60 kg on an uneven road with the single TMR’s maximum load limited to 15 kg. The experimental results demonstrate the effectiveness of the structural design and control strategies of the TMR-based MRCTS.

Graphical abstract

Keywords

multirobot system / cooperative transportation / terrain adaptability / trajectory tracking / collaborative paradigm / uneven road

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Nomenclature

Abbreviations
DOF	Degree of freedom
MCU	Microcontroller unit
MRCTS	Multirobot cooperative transportation system
OMR	Omnidirectional mobile robot
TMR	Tracked mobile robot
Wi-Fi	Wireless fidelity
Variables
Ai	Connection point between the rigid loading plate and the ith connector
bi	Half of the physical wheelbase of the ith follower robot
Ci	Connection point between the ith follower robot and the ith connector
k1, k2, k3, k4, k5, k6	Gain parameters
L	Lyapunov function of the whole system
Lb	Lyapunov function of the leader robot
Lr	Lyapunov function of all the follower robots
ri	Wheel radius of the ith follower robot
rxi, ryi	Positions of point Ai in the x and y directions, respectively
vAix, vAiy	Linear velocities of point Ai in the x and y directions, respectively
vb	Linear velocity of the virtual leader robot
vbr	Linear velocity of the reference leader robot
vi	Linear velocity of the ith follower robot
vri	Linear velocity of the ith reference follower robot
wAi	Angular velocity of point Ai
wb	Angular velocity of the virtual leader robot
wbr	Angular velocity of the reference leader robot
wi	Angular velocity of the ith follower robot
wri	Angular velocity of the ith reference follower robot
xb	Position in the x direction of the virtual leader robot in the global coordinate frame
xbe	Tracking error of the leader robot in the x direction
xbr	Position in the x direction of the reference leader robot in the global coordinate frame
xei	Tracking error of the ith follower robot in the x direction
yb	Position in the y direction of the virtual leader robot in the global coordinate frame
ybe	Tracking error of the leader robot in the y direction
ybr	Position in the y direction of the reference leader robot in the global coordinate frame
yei	Tracking error of the ith follower robot in the y direction
θb	Orientation of the virtual leader robot in the global coordinate frame
θbe	Orientation error of the leader robot
θbr	Orientation of the reference leader robot in the global coordinate frame
θei	Orientation error of the ith follower robot
θri	Target orientation of the ith follower robot
θsi	Real-time orientation of the ith follower robot
λi	Wheelbase coefficient of the ith follower robot
λie	Estimation error of the wheelbase coefficient of the ith follower robot
λip	Estimation value of the wheelbase coefficient of the ith follower robot
φli	Left wheel speed of the ith follower robot without wheelbase coefficient estimation
φliN	Left wheel speed of the ith follower robot with wheelbase coefficient estimation
φri	Right wheel speed of the ith follower robot without wheelbase coefficient estimation
φriN	Right wheel speed of the ith follower robot with wheelbase coefficient estimation
φλi	Gain parameter

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 52175237) and Beijing Municipal Science and Technology Commission, China (Grant No. Z211100004021022).

Conflict of Interest

The authors declare that they have no conflict of interest.

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