Coordinated task manipulation by nonholonomic mobile robots

Coordinated task manipulation by a group of autonomous mobile robots has received signicant research effort in the last decade. Previous studies in the area revealed that one of the main problems in the area is to avoid the collisions of the robots with obstacles as well as with other members of the group. Another problem is to come up with a model for successful task manipulation. Signicant research effort has accumulated on the denition of forces to generate reference trajectories for each autonomous mobile robots engaged in coordinated behavior. If the mobile robots are nonholonomic, this approach fails to guarantee successful manipulation of the task since the so-generated reference trajectories might not satisfy the nonholonomic constraint. In this work, we introduce a novel coordinated task manipulation model inclusive of an online collision avoidance algorithm. The reference trajectory for each autonomous nonholonomic mobile robot is generated online in terms of linear and angular velocity references for the robot; hence these references automatically satisfy the nonholonomic constraint. The generated reference velocities inevitably depend on the nature of the specied coordinated task. Several coordinated task examples, on the basis of a generic task, have been presented and the proposed model is veried through simulations

ISePorto Robotic Soccer Team: A New Player Generation

Proceedings of the Scientific Meeting of the Portuguese Robotics Open 2004This paper describes the recent modifications in ISePorto MSL robotic football team and future improvements concerning the development and evolution of the team. The robot was substantially redesigned in order to achieve high reliability, allow better control and coordination capabilities and substantial increase in perception. New mechanical and hardware redesign is presented. Motion control subsystems, new vision hardware sensor and overall architecture are described. The team redesign is done for preparation for participating in the Robocup 2004. The main goal is to achieve not only an important evolution in the team control and coordination but also increased overall reliability

Modeling and Simulation of Robots Playing Football using MA TLAB/SIMULINK

Cooperating autonomous robots are characterized as intelligent systems that combine perception, reasoning, and action to perform cooperative tasks under circumstances that are insufficiently known in advance, and changing during task execution. There are various reasons to why we should build cooperative robots. They include increasing reliability and robustness through redundancy, decreasing task completion time through parallelism and decreasing cost through simpler individual robot design. Cooperative robots can be applied in various fields such as mining, construction, planetary exploration, automated manufacturing, search and rescue missions, cleanup of hazardous waste, industrial/household maintenance, nuclear power plant decommissioning, security, and surveillance. However, in this project cooperating autonomous robots are applied in terms of robots playing football. A fully autonomous robot has the ability to gain information about the environment, work for an extended period without human intervention, move either all or parts of itself throughout its operating environment without human assistance and to avoid situations that are harmful to people, property or itself. An autonomous robot may also learn or gain new capabilities like adjusting strategies for accomplishing its task(s) or adapting to changing surrounding. Therefore this project will inculcate the criteria of autonomous robots in term of robots playing football. This study will incorporate programming using MATLAB/SIMULINK, producing mathematical models and applying control analysis methods

Landmarks as navigation - aids for multiple robots

The paper presents selected landmarks as navigation-aids or waypoints for multiple car-like robots in a contained workspace cluttered with randomly fixed obstacles and landmarks. A new metrics is designed to select specific landmarks (which are treated as waypoints) falling in the robots’ field of view and with a minimum distance away from each other and their targets. A new metric is also defined to obtain the robot’s field of view at every iteration. Using the Lyapunov-based control scheme (LbCS) nonlinear acceleration-based stabilizing control laws are derived for navigation amongst obstacles and landmarks en route the final destination via selected landmarks or waypoints. The proposed technique and the new control laws are verified via interesting computer simulations

Control and Localisation for the ISePorto Robotic Soccer Team

International Conference on Advanced Robotics, Coimbra, Portugal, Julho 2003This paper describes the control and localisation design and implementation status of the ISePorto robotic football team for participation in Robocup Middle Size League (F2000). The objectives guiding the project were the applications and research in hybrid control and coordination systems. The system has also an educational support role. A special attention is made to the custom design to allow the execution of complex manoeuvres and team coordinated behaviours. The robot has different pass, shot, and manoeuvre capabilities providing high level tactical and strategic planing and coordination

Monocular Vision as a Range Sensor

One of the most important abilities for a mobile robot is detecting obstacles in order to avoid collisions. Building a map of these obstacles is the next logical step. Most robots to date have used sensors such as passive or active infrared, sonar or laser range finders to locate obstacles in their path. In contrast, this work uses a single colour camera as the only sensor, and consequently the robot must obtain range information from the camera images. We propose simple methods for determining the range to the nearest obstacle in any direction in the robot’s field of view, referred to as the Radial Obstacle Profile. The ROP can then be used to determine the amount of rotation between two successive images, which is important for constructing a 360º view of the surrounding environment as part of map construction

A Decomposition Approach to Multi-Vehicle Cooperative Control

We present methods that generate cooperative strategies for multi-vehicle control problems using a decomposition approach. By introducing a set of tasks to be completed by the team of vehicles and a task execution method for each vehicle, we decomposed the problem into a combinatorial component and a continuous component. The continuous component of the problem is captured by task execution, and the combinatorial component is captured by task assignment. In this paper, we present a solver for task assignment that generates near-optimal assignments quickly and can be used in real-time applications. To motivate our methods, we apply them to an adversarial game between two teams of vehicles. One team is governed by simple rules and the other by our algorithms. In our study of this game we found phase transitions, showing that the task assignment problem is most difficult to solve when the capabilities of the adversaries are comparable. Finally, we implement our algorithms in a multi-level architecture with a variable replanning rate at each level to provide feedback on a dynamically changing and uncertain environment.Comment: 36 pages, 19 figures, for associated web page see http://control.mae.cornell.edu/earl/decom

Trajectory tracking and time delay management of 4-mecanum wheeled mobile robots (4-MWMR)

International audienceNowadays, wheeled mobile robots have a very important role in industrial applications, namely in transportation tasks thanks to their accuracy and rapidity. However, meeting obstacles while executing a mission can cause an important time delay, which is not appreciable in industry where production must be optimal. This paper deals with the time delay management, the trajectory generation and the tracking problem applied on four wheeled omnidirectional mobile robots. A strategy is proposed to minimize or compensate the time delay caused by obstacles. The approach is done by updating the reference trajectory. This update helps to track the trajectory in real time, a new control law based on the feedback linearization control theory is synthesized to track perfectly generated or updated trajectories

Modelling and control of the coordinated motion of a group of autonomous mobile robots

The coordinated motion of a group of autonomous mobile robots for the achievement of a coordinated task has received signifcant research interest in the last decade. Avoiding the collisions of the robots with the obstacles and other members of the group is one of the main problems in the area as previous studies have revealed. Substantial amount of research effort has been concentrated on defning virtual forces that will yield reference trajectories for a group of autonomous mobile robots engaged in coordinated behavior. If the mobile robots are nonholonomic, this approach fails to guarantee coordinated motion since the nonholonomic constraint blocks sideway motions. Two novel approaches to the problem of modeling coordinated motion of a group of autonomous nonholonomic mobile robots inclusive of a new collision avoidance scheme are developed in this thesis. In the first approach, a novel coordination method for a group of autonomous nonholonomic mobile robots is developed by the introduction of a virtual reference system, which in turn implies online collision-free trajectories and consists of virtual mass-spring-damper units. In the latter, online generation of reference trajectories for the robots is enabled in terms of their linear and angular velocities. Moreover, a novel collision avoidance algorithm, that updates the velocities of the robots when a collision is predicted, is developed in both of the proposed models. Along with the presentation of several coordinated task examples, the proposed models are verifed via simulations. Experiments were conducted to verify the performance of the collision avoidance algorithm