Adaptive Behaviors in Autonomous Navigation with Collision Avoidance and Bounded Velocity of an Omnidirectional Mobile Robot

2017 ◽  
Vol 92 (2) ◽  
pp. 359-380 ◽  
Author(s):  
Eddie Clemente ◽  
Marlen Meza-Sánchez ◽  
Eusebio Bugarin ◽  
Ana Yaveni Aguilar-Bustos
Keyword(s):  
Mobile Robot ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Adaptive Behaviors ◽  
Omnidirectional Mobile Robot

scholarly journals Motion Planning and Control of an Omnidirectional Mobile Robot in Dynamic Environments

Robotics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 48
Author(s):  
Mahmood Reza Azizi ◽  
Alireza Rastegarpanah ◽  
Rustam Stolkin
Keyword(s):  
Mobile Robot ◽  
Collision Avoidance ◽  
Motion Control ◽  
Equations Of Motion ◽  
Dynamic Environments ◽  
Discrete State ◽  
Omnidirectional Mobile Robot ◽  
Planning And Control ◽  
Avoidance Strategy ◽  
And Performance

Motion control in dynamic environments is one of the most important problems in using mobile robots in collaboration with humans and other robots. In this paper, the motion control of a four-Mecanum-wheeled omnidirectional mobile robot (OMR) in dynamic environments is studied. The robot’s differential equations of motion are extracted using Kane’s method and converted to discrete state space form. A nonlinear model predictive control (NMPC) strategy is designed based on the derived mathematical model to stabilize the robot in desired positions and orientations. As a main contribution of this work, the velocity obstacles (VO) approach is reformulated to be introduced in the NMPC system to avoid the robot from collision with moving and fixed obstacles online. Considering the robot’s physical restrictions, the parameters and functions used in the designed control system and collision avoidance strategy are determined through stability and performance analysis and some criteria are established for calculating the best values of these parameters. The effectiveness of the proposed controller and collision avoidance strategy is evaluated through a series of computer simulations. The simulation results show that the proposed strategy is efficient in stabilizing the robot in the desired configuration and in avoiding collision with obstacles, even in narrow spaces and with complicated arrangements of obstacles.

scholarly journals Autonomous Navigation Using Deep Reinforcement Learning in ROS

2021 ◽  
Vol 11 (2) ◽  
pp. 63-70
Author(s):  
Ganesh Khekare ◽  
Shahrukh Sheikh
Keyword(s):  
Reinforcement Learning ◽  
Mobile Robot ◽  
Social Norms ◽  
Collision Avoidance ◽  
Human Behavior ◽  
Autonomous Navigation ◽  
Autonomous Robot ◽  
Stochastic Behavior ◽  
Human Behaviors ◽  
Navigation Scheme

For an autonomous robot to move safely in an environment where people are around and moving dynamically without knowing their goal position, it is required to set navigation rules and human behaviors. This problem is challenging with the highly stochastic behavior of people. Previous methods believe to provide features of human behavior, but these features vary from person to person. The method focuses on setting social norms that are telling the robot what not to do. With deep reinforcement learning, it has become possible to set a time-efficient navigation scheme that regulates social norms. The solution enables mobile robot full autonomy along with collision avoidance in people rich environment.

Kinematics Study on an Omnidirectional Mobile Robot with MY Wheels

ROBOT ◽  
2012 ◽  
Vol 34 (2) ◽  
pp. 144 ◽  
Author(s):  
Changlong YE ◽  
Huaiyong LI ◽  
Shugen MA ◽  
Huichao NI
Keyword(s):  
Mobile Robot ◽  
Omnidirectional Mobile Robot

scholarly journals A novel navigation system for an autonomous mobile robot in an uncertain environment

Robotica ◽  
2021 ◽  
pp. 1-26
Author(s):  
Meng-Yuan Chen ◽  
Yong-Jian Wu ◽  
Hongmei He
Keyword(s):  
Mobile Robot ◽  
Navigation System ◽  
Autonomous Navigation ◽  
Clustering Algorithm ◽  
Modular Design ◽  
Optimal Path ◽  
Surrounding Environment ◽  
Computing Complexity ◽  
The Arts ◽  
Window Approach

Abstract In this paper, we developed a new navigation system, called ATCM, which detects obstacles in a sliding window with an adaptive threshold clustering algorithm, classifies the detected obstacles with a decision tree, heuristically predicts potential collision and finds optimal path with a simplified Morphin algorithm. This system has the merits of optimal free-collision path, small memory size and less computing complexity, compared with the state of the arts in robot navigation. The modular design of 6-steps navigation provides a holistic methodology to implement and verify the performance of a robot’s navigation system. The experiments on simulation and a physical robot for the eight scenarios demonstrate that the robot can effectively and efficiently avoid potential collisions with any static or dynamic obstacles in its surrounding environment. Compared with the particle swarm optimisation, the dynamic window approach and the traditional Morphin algorithm for the autonomous navigation of a mobile robot in a static environment, ATCM achieved the shortest path with higher efficiency.

An RPLiDAR based SLAM equipped with IMU for Autonomous Navigation of Wheeled Mobile Robot

2020 ◽  
Author(s):  
Muhammad Saad Aslam ◽  
Muhammad Irfan Aziz ◽  
Kanwal Naveed ◽  
Uzair Khaleeq uz Zaman
Keyword(s):  
Mobile Robot ◽  
Autonomous Navigation ◽  
Wheeled Mobile Robot

scholarly journals COLREG-Compliant Optimal Path Planning for Real-Time Guidance and Control of Autonomous Ships

2021 ◽  
Vol 9 (4) ◽  
pp. 405
Author(s):  
Raphael Zaccone
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Collision Avoidance ◽  
Autonomous Navigation ◽  
Optimal Path ◽  
Open Water ◽  
Optimal Path Planning ◽  
Guidance And Control ◽  
Real Time Applications ◽  
And Control

While collisions and groundings still represent the most important source of accidents involving ships, autonomous vessels are a central topic in current research. When dealing with autonomous ships, collision avoidance and compliance with COLREG regulations are major vital points. However, most state-of-the-art literature focuses on offline path optimisation while neglecting many crucial aspects of dealing with real-time applications on vessels. In the framework of the proposed motion-planning, navigation and control architecture, this paper mainly focused on optimal path planning for marine vessels in the perspective of real-time applications. An RRT*-based optimal path-planning algorithm was proposed, and collision avoidance, compliance with COLREG regulations, path feasibility and optimality were discussed in detail. The proposed approach was then implemented and integrated with a guidance and control system. Tests on a high-fidelity simulation platform were carried out to assess the potential benefits brought to autonomous navigation. The tests featured real-time simulation, restricted and open-water navigation and dynamic scenarios with both moving and fixed obstacles.

scholarly journals Autonomous Control for an Omnidirectional Mobile Robot with the Orthogonal-Wheel Assembly.

1999 ◽  
Vol 17 (1) ◽  
pp. 51-60 ◽  
Author(s):  
Jun Tang ◽  
Keigo Watanabe ◽  
Katsutoshi Kuribayashi ◽  
Yamato Shiraishi
Keyword(s):  
Mobile Robot ◽  
Autonomous Control ◽  
Omnidirectional Mobile Robot
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