Zhenmin Tang

A Visibility-based Algorithm for Multi-robot Boundary Coverage

Cell decomposition is often used in autonomous area coverage. We propose a visibility-based decomposition algorithm for single robot boundary coverage and a corresponding multi-robot algorithm in unknown environment. A graph data structure is exploited for completeness of coverage and incremental description of partially observed world. Visibility-based decomposition facilitates the construction of graph and algorithms operated on it. In the context of multi-robot, a dynamically selected highest priority robot is in charge of information share and synchrony through communication, polygon set operations provide tools for environmental information mergence, a distributed algorithm for multi-robot boundary coverage is proposed based on those technologies. Finally the experimental results show the relationships between robot number and traversable gate number, some future subjects of researches are introduced.

A Descriptive Model of Robot Team and the Dynamic Evolution of Robot Team Cooperation

At present, the research on robot team cooperation is still in qualitative analysis phase and lacks the description model that can quantitatively describe the dynamical evolution of team cooperative relationships with constantly changeable task demand in Multi-robot field. First this paper whole and static describes organization model HWROM of robot team, then uses Markov course and Bayesian theorem for reference, dynamical describes the team cooperative relationships building. Finally from cooperative entity layer, ability layer and relative layer we research team formation and cooperative mechanism, and discuss how to optimize relative action sets during the evolution. The dynamic evolution model of robot team and cooperative relationships between robot teams proposed and described in this paper can not only generalize the robot team as a whole, but also depict the dynamic evolving process quantitatively. Users can also make the prediction of the cooperative relationship and the action of the robot team encountering new demands based on this model.

Maximum Likelihood Estimation of Monocular Optical Flow Field for Mobile Robot Ego-motion

This paper presents an optimized scheme of monocular ego-motion estimation to provide location and pose information for mobile robots with one fixed camera. First, a multi-scale hyper-complex wavelet phase-derived optical flow is applied to estimate micro motion of image blocks. Optical flow computation overcomes the difficulties of unreliable feature selection and feature matching of outdoor scenes; at the same time, the multi-scale strategy overcomes the problem of road surface self-similarity and local occlusions. Secondly, a support probability of flow vector is defined to evaluate the validity of the candidate image motions, and a Maximum Likelihood Estimation (MLE) optical flow model is constructed based not only on image motion residuals but also their distribution of inliers and outliers, together with their support probabilities, to evaluate a given transform. This yields an optimized estimation of inlier parts of optical flow. Thirdly, a sampling and consensus strategy is designed to estimate the ego-motion parameters. Our model and algorithms are tested on real datasets collected from an intelligent vehicle. The experimental results demonstrate the estimated ego-motion parameters closely follow the GPS/INS ground truth in complex outdoor road scenarios.

Design and Development of Multi-Robot Architecture and Decision-Making Model

To design individual robot architecture in task-oriented multi-robot system running in dynamic environment, it is essential to give prominence to robot abilities of real-time reaction, making decision ability and the cooperation. However, these abilities, especially the second one, were not emphasized in the existent architectures. In this research, a hybrid robot architecture based on five reaction layers was proposed. A decision-making development method was presented. After pointing out that when a robot being able to satisfy multi-task needing, it not only need to consider the distances, but need to synthetically consider the tasks, environment, and robots self-status also, a task team selecting algorithm using decision-making matrix based on the multiple properties was further proposed. And at last test results of garbage treatment in simple simulated environment shows that method proposed in this paper is efficiency.

Planning and control strategies of multiple mobile robot moving in column formation

The main objective of this paper is to study the control problem for a multiple mobile robot team moving in the outdoor environment. In studying multi-robots how to make their formation from random original state into one line shape pass column shape area, we used a combination of centralized and distributed mechanism. First system designs path planning for every robot and formation control planning off-line based on centralized strategy. When robot will arise collision in moving, every robot plans its motion character respectively and design collision-avoidance control strategy using priority strategy based on distributed approach. After time period T, the system will get to a steady formation station. Then the robots move to the goal remaining the steady station. This method makes the system architecture concise, reduces moving blindness and increases system commonness. The method will insure robot team moving safely. At last, the emulation result is given and analyzed.