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

The Coordination of Multiple UAVs for Engaging Multiple Targets in a Time-Optimal Manner

This paper presents a solution to the real-time control of cooperative Unmanned Air Vehicles (UAVs) that engage multiple targets in a time-optimal manner. Techniques to dynamically allocate vehicles to targets and to find the time-optimal control actions of vehicles are proposed. The effectiveness of the time-optimal control technique is first demonstrated through numerical examples. The proposed strategy is then applied to a practical battlefield problem where ten vehicles are required to engage four targets, and numerical results show the efficiency of the proposed strategy

Time-optimal coordinated control of the relative formation of multiple vehicles

© 2003 IEEE. This paper presents a solution to the time-optimal control of the relative formation of multiple vehicles. This is a problem in cooperative time-optimal control with a free terminal state constraint. In this paper, a canonical formulation of the problem is first derived. Then, a numerical technique to solve this class of problem is proposed. Numerical results demonstrate the efficacy of the proposed formulation and solution to the problem of expeditiously building and controlling formations of cooperative autonomous vehicles

Parallel grid-based method and belief fusion Real-time cooperative non-Gaussian estimation

This paper presents a parallel grid-based method and belief fusion for real-time cooperative Bayesian estimation. The grid-based recursive Bayesian estimation (RBE) method effectively maintains the belief of objects even with no detection event but requires large computation for its prediction and correction processes as well as fusion process in cooperative estimation. In order for real-time estimation, the belief fusion proposed in the paper carries out the fusion of belief outside the RBE loop. The parallelization of the entire grid-based method and belief fusion further accelerates the RBE so that real-time estimation is possible even in highly dynamical environments. Numerical examples have first demonstrated the validity of the proposed approach through parametric studies. The proposed approach was then applied to the cooperative search by autonomous unmanned ground vehicles (UGVs), and its real-time capability has been demonstrated. © 2011 IEEE

A time-optimal control strategy for pursuit-evasion games problems

This paper presents a control strategy for the pursuer in the pursuit-evasion game problem when the evader behaves intelligently. The pursuer in the proposed technique does not try to react to the evader's behavior instantaneously. The proposed technique therefore does not yield instantaneous optimality but capture the evader in a time-efficient and robust fashion even when the evader is intelligent. The proposed technique was applied to two numerical examples and the results were compared to those by the conventional motion tracking algorithms. The results and comparison show that the proposed technique could capture the evader faster than the conventional motion tracking algorithms in both the examples

Dynamic allocation and control of coordinated UAVs to engage multiple targets in a time-optimal manner

This paper presents the real-time control of cooperative Unmanned Air Vehicles (UAVs) that dynamically engage multiple targets in a time-optimal manner. Techniques to dynamically allocate vehicles to targets and to subsequently find the time-optimal control actions are proposed. The decentralization of the proposed control strategy is further presented such that the vehicles can be controlled in real-time without significant time delay. The proposed strategy is then applied to various practical battlefield problems, and numerical results show the efficiency of the proposed strategy

Control issues of an autonomous vehicle

This paper addresses some control issues of a robotic amphibious vehicle that can serve as a general framework for automation of tractors used in construction. These include the vehicle's low-level dynamic equations, the development of its braking control system, kinematics in interactions with ground and the slip problem. Simulation and real-time results to date are presented