This article focuses on the luggage trolley transportation problem, an essential part of robotic autonomous luggage trolley collection. To efficiently address the nonholonomic constraints derived from the formation of two collaborative robots and a queue of luggage trolleys, we propose a comprehensive framework consisting of a global planning method and a real-time divide-and-conquer control strategy. The popular Hybrid A* algorithm generates a feasible path as the global planner. A model predictive controller is designed to track this path stably and in real time. To maintain the formation so that the whole queue of robots and luggage trolleys does not split, a safety filter that consists of a discrete-time control Lyapunov function and a decentralized control barrier function is implemented in the transportation process. Finally, we conduct real-world experiments to verify the effectiveness of the proposed method on three representative paths, and the results show that our approach can achieve robust performance. The demonstration video can be found at https://www.youtube.com/watch?v=iPiT8BfLIpU.

This paper introduces an approach of collaborative control for individual robots to collaboratively perform a common task, without the need for a centralized controller to coordinate the group. The approach is illustrated by an application example involving multiple robots performing a collaborative task to achieve a common goal. The objective of this example problem is to control multiple robots that are connected to an object through elastic cables in order to bring the object to a target position. There is no communication between the robots, and hence each robot is unaware of how the other robots are going to react at any instant. Only the information pertaining to the object and the target is available to all the robots at any instant. Genetic fuzzy system (GFS) is used to develop controller for each of the robots. The nonlinearity of fuzzy logic systems coupled with the search capability of genetic algorithms provides a tool to design controllers for such collaborative tasks. A set of training scenarios are developed to train the individual robot controllers for this task. The trained controllers are then tested on an extensive set of scenarios. This paper describes the development process of GFS controllers for dynamic case involving systems consisting of three robots. It is also shown that the GFS controllers are scalable for the more complex systems involving more than three robots.

Trajectory tracking of a mobile manipulator in the Cartesian space based on decentralized control is considered in this paper. The dynamic model is first rearranged to take the form of two interconnected subsystems with constraint flow, namely, a nonholonomic mobile platform subsystem and a holonomic manipulator subsystem. Secondly, using the inverse kinematics, the workspace desired trajectory of the mobile manipulator is transformed to the manipulator joint space as well as the platform desired trajectory. The kinematic control is developed from the desired trajectory of the platform. Then, the desired velocity is derived using the kinematic controller of the mobile platform, after which the velocity is used to obtain the control law of the mobile platform subsystem. Thirdly, the control law of the manipulator subsystem is developed based on the desired and real values of the manipulator, as well as the desired velocity. According to the Lyapunov stability theory, the proposed decentralized control strategy guarantees the global stability of the closed-loop system, and the tracking errors are bounded. Experimental results obtained on a 3-DOF manipulator mounted on a mobile platform are given to demonstrate the feasibility and effectiveness of the proposed approach. This is confirmed by a comparison with the computed torque approach.

Several non-holonomic Dubins-car-like robots travel over paths with bounded curvatures in a plane that contains an a priori unknown region. The robots are anonymous to one another and do not use communication facilities. Any of them has access to the current minimum distance to the region and can determine the relative positions and orientations of the other robots within a finite and given visibility range. We present a distributed navigation and guidance strategy under which every robot autonomously converges to the desired minimum distance to the region with always respecting a given safety margin, the robots do not collide with one another and do not get into clusters, and the entire team ultimately sweeps over the respective equidistant curve at a speed exceeding a given threshold, thus forming a kind of a sweeping barrier at the perimeter of the region. Moreover, this strategy provides effective sub-uniform distribution of the robots over the equidistant curve. Mathematically rigorous justification of the proposed strategy is offered; its effectiveness is confirmed by extensive computer simulations and experiments with real wheeled robots.

We study a problem of K-barrier coverage by employing a network of self-deployed, autonomous mobile robotic sensors. A decentralized coordination algorithm is proposed for the robotic sensors to address the coverage problem. The algorithm is developed based on some simple rules that only rely on local information. By applying the algorithm to the robotic sensors, K layers of sensor barriers are formed to cover the region between two given points. To illustrate the proposed algorithm, numerical simulations are carried out for a number of scenarios.

Based on the author's knowledge the paper gives a brief account of some of the scientific achievements of robotics that were of crucial importance to its development.

In a rough chronological order these are: zero-moment concept and semi-inverse method; recursive formulation of robot dynamics; computer-aided derivation of robot dynamics in symbolic form; dynamic approach to generation of trajectories of robotic manipulators; centralized feedforward control in robotics; robot dynamic control; decentralized control and observer applied to strongly coupled active mechanisms; force feedback in dynamic control of robots; decentralized control stability tests for robotic mechanisms; underactuated robotic systems; practical stability tests in robotics; unified approach to control laws synthesis for robot interacting with dynamic environment; modeling and control of multi-arm cooperating robots interacting with environment; connectionist algorithms for advanced learning control of robots interacting with dynamic environment; fuzzy logic robot control with model-based dynamic compensation, and internal redundancy – a new way to improve robot dynamic performance.

This paper introduces an event-based decentralized control scheme for the cooperation between multiple manipulators. This is in contrast to the common practice of using only centralized controls for such cooperation which, consequently, greatly limit the flexibility of robotic systems. The manipulators used in the present system are very simple with only two degrees of freedom, while even one of them is passive. Moreover these manipulators use very few and commonly available sensors only. Computer simulations indicated the applicability of the event-based decentralized control scheme for multi-manipulator cooperation, while real-life experimental implementation has proved that the proposed decentralized control scheme is fairly applicable for very simple and even under-actuated systems too. Hence, this work has opened new doors towards further research in this area. The proposed control scheme is expected to be equally applicable for any mobile or immobile multi-robotic system.

In this paper we present an experimental comparison between different decentralized controllers for industrial robot manipulators. In spite of the fact that robot manipulators are highly nonlinear and coupled multivariable systems, decentralized controllers have been widely adopted in industrial environments for trajectory tracking, because of their simplicity and their fault tolerance feature. Different kinds of controllers have been investigated: the typical PID-based controller, a nonlinear three-term controller devised by Tarokh, and a variable structure control law, a discontinuous integral control, both in the continuous and in the discretised version. Allowances are made for the tuning of the parameters in order to obtain low tracking errors. Results show that better performances are obtained by controllers other than PID, especially by the discontinuous integral control, so that they appear to be particularly appropriate for the use in industrial robots.