Papers by Keyword: Mobile Robot

Abstract: Multi-sensor information fusion is that fuses information of multiple sensors gained through use of redundant, complementary, or timelier information in a system can provide more reliable and accurate information. Under the research of mobile robot environmental information, a control method of fuzzy neural network based on T-S (Takagi-Sugeno) type is given, it can fuses effectively collected information from multiple ultrasonic sensors and a CCD camera, and realize the real-time control for mobile robot. The results on mobile robot obstacles avoidance verified the effectiveness of the method.

Abstract: To avoid injury with the coexistence of human and mobile robot in the circumstance, a vision-based system for mobile robot/human localization is designed and implemented. The details of the system are described in this paper.

Abstract: Mobile robot is an intelligent system which can move freely and is scheduled to complete the task in the working environment. Obstacle avoidance of mobile robot is the research hotspot in the control field of the mobile robot. The mobile robot obstacle avoidance methods are classified, including the traditional algorithms and the intelligent algorithms. This paper summarizes the intelligent algorithm in the mobile robot obstacle avoidance technique in the present situation, and the intelligent algorithm which is the most researched in the current. Finally, this paper prospects the development trend of intelligent obstacle avoidance of the robot.

Abstract: Multi-sensor Information Fusion can get more accurate information required by the system through fusing redundant, complementary, or more real-time information provided by multiple sensors. This paper, with the emphasis on the MIF technology, combining its application in mobile robots, is discussed from two aspects, namely theory and simulation experiments. First of all, this paper expounds the basic principle of MIF technology, systematic structure and gradation of information fusion and information fusion methods; Secondly, based on the theory of neural network integration, it discusses the application of MIF technology in the field of robots , providing an effective method for navigation and obstacle avoidance of mobile robots.

Abstract: The autonomous ability of the system, which enables it to park itself without any human interference, finds its application mostly in automobile industry. Though the basic algorithm of autonomous parking is relatively simple, the question of reliability and accuracy of parking can be quite complicated. The mathematical models developed theoretically and simulated numerically not always can in the same accurate way perform in a real vehicle. One of the main reasons for it is the interplay between the controlling system and mechanical structure of the vehicle. To investigate this problem the car-type robot simulating the specific features of the mechanical structure of the real car was developed. It was used for verification of few parking approaches proposed in the literature. A parking algorithm was proposed and programmed for a developed car-type robot. The experimental comparison between theoretically calculated and actually observed values of main parking parameters was done and analysed. The approach of optimization of parking strategy from the view point of minimization of positioning errors was proposed and tested.

Abstract: By applying data fusions from GPS and MEMS sensors to plan and track path, and achieve the goal of mobile robot autonomous navigation. An improved filtering method based on Sage_Husa filtering is described, which can effectively restrain the filtering divergence, improve dynamic performance of filter, enhance stability and adaptability of filter, and improve navigation precision. With fuzzy adaptive PID control, the stability of control system is guaranteed with control strategy adjustment in real time. Finally, it is programmed that converting the fusion of high-precision GPS and attitude information into control command so as to succeed in robot navigation and real-time display on map. The feasibility and effectiveness of methods described above are verified and proved by experiments and MATLAB simulation.

Abstract: The mobile robot's traveling path is generally made up of line and curve segments, so moving process often requires frequent stops to change the wheel steering angle to alter the direction of motion, which is lack of flexibility. In this paper, the use of the continuous-curvature curve algorithm (CCCA) solves the mutant problem of the mobile robot steering angle at turns. It can connect two line segments path so that the mobile robot achieves continuous deflection in swerve process, and it also can achieve a smooth shift within the steering angle 80^o.

Abstract: This paper proposes a 3D environment mapping and pothole detection system by using a laser range finder for a mobile robot. The robot also equips two rotary encoders and an inertial measurement unit to deal with dead reckoning (DR). Through the coordinate transform method from 2D to 3D, each point in 3D coordinate could be calculated. This method is called mobile mapping system (MMS). In addition, the result for road damage is often caused by potholes. Therefore, the pothole detection is considered here by using a laser range finder and a camera. A human-machine interface is designed to record the data on the road including the location and environment. The experiment has been tested on the university road.

Abstract: Proposed an uncertain environment path planning method for mobile robot in the presence of moving obstacles. Combining the global planning with the local planning, this dissertation presents a new approach to on-line real-time path planning with respect to the dynamic uncertain environment. With current sampling position, the autoregressive model predicts motion trajectories of moving obstacles. And the predicted positions are treated as instantaneously static. So moving obstacles in the predicted positions can be considered as static in the path planning process. Simulation examples demonstrated the effectiveness, feasibility, real-time capability, high stability and perfect performance of obstacle avoidance.

Abstract: It is very difficult for hopping robots to follow the trajectory without controlling hopping angle. A hopping angle controller is designed for combustion piston type hopping robot to adjust the angle of hop which is required to achieve a desired distance or height. So, the controller adds functionality to hopping robot for altering the hopping angle during operation according to obstacle height and obstacle distance. A proportional Integrated Derivative (PID) and Linear Quadratic Regulator (LQR) are designed and compared for adjusting hopping angle by using MATLAB / SIMULINK environment. As result, both controllers are capable to control hopping angle but PID gives better performance. An implementation of PID controller for the hopping angle control is given by using a DC motor. The experiment also carried out on prototype by using PID controller and found satisfactory results.