scholarly journals Motion Planning of Multiple Mobile Robots Using Virtual Impedance

1996 ◽  
Vol 8 (1) ◽  
pp. 67-74 ◽  
Author(s):  
Tamio Arai ◽  
◽  
Jun Ota
Keyword(s):  
Mobile Robot ◽  
Motion Planning ◽  
Mobile Robots ◽  
Lower Layer ◽  
Local Equilibrium ◽  
Current Position ◽  
Cooperative Motion ◽  
Robot Systems ◽  
Simulation Results ◽  
Virtual Impedance

This paper proposes a planning method for multiple mobile robot systems. It has two characteristics: (1) Each robot plans a path on its own, without any supervisor; (2) The concept of cooperative motion can be implemented. A two-layered hierarchy is defined for a scheme of individual path planning. The higher layer generates a trajectory from the current position to a goal. The lower layer called“Virtual Impedance Metho” makes a real-time plan to follow the generated trajectory while avoiding obstacles and avoiding or cooperating with other robots. This layer is composed of four modules called, “watchdog”, “deadlock solver”,“blockade solver”, and “pilot”. The local equilibrium is detected by the watchdog and cancelled by the deadlock solver or the blockade solver. Simulation results indicate the effectiveness of the proposed method.

Path Following System for Cooperative Mobile Robots

2010 ◽  
Vol 166-167 ◽  
pp. 161-166
Author(s):  
Ionut Dinulescu ◽  
Dorin Popescu ◽  
Mircea Nitulescu ◽  
Alice Predescu
Keyword(s):  
Artificial Intelligence ◽  
Mobile Robots ◽  
Path Following ◽  
Path Generation ◽  
Cooperative Robots ◽  
Generation System ◽  
Robot Systems ◽  
Simulation Results ◽  
Trajectory Generator

Recent advances in the domains of social and life artificial intelligence have constituted the basis for a new discipline that studies cooperation in multi-robot systems and its utility in applications where some tasks cannot be carried out by a single robot. This paper introduces a trajectory generator which is used for determination of the most appropriate trajectory which a robot needs to track in order to perform different tasks specific to cooperative robots, such as moving in a given formation or pushing an object to a given destination. Different algorithms are described in this paper, starting from simple polyline and circular paths to complex Bezier trajectories. Simulation results of the proposed path generation system are also provided, along with the description of its implementation on real mobile robots. An implementation of real robots is also presented in this paper.

scholarly journals The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation

2020 ◽  
Vol 69 ◽  
pp. 471-500
Author(s):  
Shih-Yun Lo ◽  
Shiqi Zhang ◽  
Peter Stone
Keyword(s):  
Mobile Robot ◽  
Motion Planning ◽  
Mobile Robots ◽  
Large Scale ◽  
Accurate Estimate ◽  
Indoor Environments ◽  
Task Planning ◽  
Trade Offs ◽  
High Level ◽  
Task Level

Intelligent mobile robots have recently become able to operate autonomously in large-scale indoor environments for extended periods of time. In this process, mobile robots need the capabilities of both task and motion planning. Task planning in such environments involves sequencing the robot’s high-level goals and subgoals, and typically requires reasoning about the locations of people, rooms, and objects in the environment, and their interactions to achieve a goal. One of the prerequisites for optimal task planning that is often overlooked is having an accurate estimate of the actual distance (or time) a robot needs to navigate from one location to another. State-of-the-art motion planning algorithms, though often computationally complex, are designed exactly for this purpose of finding routes through constrained spaces. In this article, we focus on integrating task and motion planning (TMP) to achieve task-level-optimal planning for robot navigation while maintaining manageable computational efficiency. To this end, we introduce TMP algorithm PETLON (Planning Efficiently for Task-Level-Optimal Navigation), including two configurations with different trade-offs over computational expenses between task and motion planning, for everyday service tasks using a mobile robot. Experiments have been conducted both in simulation and on a mobile robot using object delivery tasks in an indoor office environment. The key observation from the results is that PETLON is more efficient than a baseline approach that pre-computes motion costs of all possible navigation actions, while still producing plans that are optimal at the task level. We provide results with two different task planning paradigms in the implementation of PETLON, and offer TMP practitioners guidelines for the selection of task planners from an engineering perspective.

HOLONOMIC AND OMNIDIRECTIONAL LOCOMOTION SYSTEMS FOR WHEELED MOBILE ROBOTS: A REVIEW

2015 ◽  
Vol 77 (28) ◽  
Author(s):  
M. Juhairi Aziz Safar
Keyword(s):  
Mobile Robot ◽  
Mobile Robots ◽  
Degrees Of Freedom ◽  
Wheeled Mobile Robot ◽  
Arbitrary Direction ◽  
Current Position ◽  
Wheeled Mobile Robots ◽  
Future Improvement ◽  
Position And Orientation ◽  
Three Degrees Of Freedom

Holonomic and omnidirectional locomotion systems are best known for their capability to maneuver at any arbitrary direction regardless of their current position and orientation with a three degrees of freedom mobility. This paper summarizes the advancement of holonomic and omnidirectional locomotion systems for wheeled mobile robot applications and discuss the issues and challenges for future improvement.

Two-level artificial intelligent system of mobile robot motion planning

2014 ◽  
Vol 10 ◽  
pp. 50-54
Author(s):  
O.V. Darintsev ◽  
A.B. Migranov
Keyword(s):  
Mobile Robot ◽  
Motion Planning ◽  
Mobile Robots ◽  
Control Systems ◽  
Intelligent System ◽  
Robot Motion ◽  
Robot Motion Planning ◽  
Vision Systems ◽  
Artificial Intelligent ◽  
Upper Level

We consider a two-level intelligent system for planning the movements of mobile robots, in which the search for the trajectory is carried out on two levels — a rough and precise planning subsystems. Insufficient resolution of vision systems at the upper level is compensated by sensor systems placed on board robots. The proposed approach reduces the resources required on-board control systems (are based on computer or controller) and optimization of traffic routes of all members of the group to achieve group goals.

Decision Making for a Mobile Robot Using Potential Function

2007 ◽  
Vol 19 (3) ◽  
pp. 298-307 ◽  
Author(s):  
Kazumi Oikawa ◽  
◽  
Hidenori Takauji ◽  
Takanori Emaru ◽  
Takeshi Tsuchiya ◽  
...  
Keyword(s):  
Decision Making ◽  
Mobile Robot ◽  
Potential Function ◽  
State Transition ◽  
Lower Layer ◽  
Object Oriented ◽  
Subsumption Architecture ◽  
Object Oriented Design ◽  
Event Driven ◽  
Simulation Results

We discuss decision making for a behavior-based robot with modules which determining robot action. The subsumption architecture (SA) arranges modules in layers, giving upper-layer module action priority over lower-layer modules. Although implementation is easy, results in many inefficient actions because upper-layer module are used regardless of other modules. We solve this problem by representing actions by Potential Function (PF), in which maximum votes are collected from modules. Using event-driven state transition, the robot decides its action with appropriate sets of modules changed based on the situation. We apply this to navigation tasks in a corridor and show simulation results. When we give a map and path designation to the robot, we use a handwriting map interface. We compare object-oriented design SA and PMF with our proposal and show how inefficient actions are reduced using our proposal.

Development of Sensor-Based Navigation for Mobile Robots Using Target Direction Sensor

1999 ◽  
Vol 11 (1) ◽  
pp. 39-44 ◽  
Author(s):  
Motoji Yamamoto ◽  
◽  
Nobuhiro Ushimi ◽  
Akira Mohri
Keyword(s):  
Measurement Error ◽  
Mobile Robot ◽  
Motion Planning ◽  
Mobile Robots ◽  
Navigation System ◽  
Location Information ◽  
Work Space ◽  
Target Direction ◽  
Navigation Algorithm ◽  
Direction Information

Sensor-based navigation used a target direction sensor for mobile robots among unknown obstacles in work space is discussed. The advantage of target direction information is robustness of measurement error for online navigation, compared to robot location information. Convergence of navigation using target direction information is discussed. An actual sensor system using two CdS sensors to measure target direction is proposed. Using target direction information, we present a new sensor based navigation algorithm in unknown obstacle environment. The navigation algorithm is based on target direction information, unlike sensor-based motion planning algorithms based on mobile robot location information. Using a sensor-based navigation system, we conducted a navigation experiment and simulations in unknown obstacle environment.

Virtual Reality based Mobile Robot Navigation in Greenhouse Environment

2017 ◽  
Vol 8 (2) ◽  
pp. 854-859
Author(s):  
M. Saiful Azimi ◽  
Z. A. Shukri ◽  
M. Zaharuddin
Keyword(s):  
Virtual Reality ◽  
Mobile Robot ◽  
Mobile Robots ◽  
Virtual Environment ◽  
Robot Navigation ◽  
Tracking Error ◽  
Mobile Robot Navigation ◽  
Probabilistic Roadmap ◽  
Time Distance ◽  
Simulation Results

The difficulties of transporting heavy mobile robots limit robotic experiments in agriculture. Virtual reality however, offers an alternative to conduct experiments in agriculture. This paper presents an application of virtual reality in a robot navigational experiment using SolidWorks and simulated into MATLAB. Trajectories were initiated using Probabilistic Roadmap and compared based on travel time, distance and tracking error, and the efficiency was calculated. The simulation results showed that the proposed method was able to conduct the navigational experiment inside the virtual environment. U-turn trajectory was chosen as the best trajectory for crop inspection with 82.7% efficiency.

Special Issue on Modern Trends in Mobile Robotics

2002 ◽  
Vol 14 (4) ◽  
pp. 323-323
Author(s):  
Takashi Tsubouchi ◽  
◽  
Keiji Nagatani ◽  
Keyword(s):  
Mobile Robot ◽  
Motion Planning ◽  
Mobile Robots ◽  
High Speed ◽  
Mobile Robotics ◽  
Low Cost ◽  
Electronic Devices ◽  
Mobile Robot Navigation ◽  
Map Building ◽  
Special Issue

Since the dawning of the Robotics age, mobile robots have been important objectives of research and development. Working from such aspects as locomotion mechanisms, path and motion planning algorithms, navigation, map building and localization, and system architecture, researchers are working long and hard. Despite the fact that mobile robotics has a shorter history than conventional mechanical engineering, it has already accumulated a major, innovative, and rich body of R&D work. Rapid progress in modern scientific technology had advanced to where down-sized low-cost electronic devices, especially highperformance computers, can now be built into such mobile robots. Recent trends in ever higher performance and increased downsizing have enabled those working in the field of mobile robotics to make their models increasingly intelligent, versatile, and dexterous. The down-sized computer systems implemented in mobile robots must provide high-speed calculation for complicated motion planning, real-time image processing in image recognition, and sufficient memory for storing the huge amounts of data required for environment mapping. Given the swift progress in electronic devices, new trends are now emerging in mobile robotics. This special issue on ""Modern Trends in Mobile Robotics"" provides a diverse collection of distinguished papers on modern mobile robotics research. In the area of locomotion mechanisms, Huang et al. provide an informative paper on control of a 6-legged walking robot and Fujiwara et al. contribute progressive work on the development of a practical omnidirectional cart. Given the importance of vision systems enabling robots to survey their environments, Doi et al., Tang et al., and Shimizu present papers on cutting-edge vision-based navigation. On the crucial subject of how to equip robots with intelligence, Hashimoto et al. present the latest on sensor fault detection in dead-reckoning, Miura et al. detail the probabilistic modeling of obstacle motion during mobile robot navigation, Hada et al. treat long-term mobile robot activity, and Lee et al. explore mobile robot control in intelligent space. As guest editors, we are sure readers will find these articles both informative and interesting concerning current issues and new perspectives in modern trends in mobile robotics.

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