scholarly journals Smooth Autonomous Navigation Considering Avoidance Behavior Characteristics of Pedestrians

2022 ◽  
Author(s):  
Ryunosuke Harada ◽  
Hiroshi Yoshitake ◽  
Motoki Shino
Keyword(s):  
Angular Velocity ◽  
Path Planning ◽  
Avoidance Behavior ◽  
Autonomous Navigation ◽  
Personal Mobility ◽  
Planning Strategy ◽  
Short Period ◽  
Behavior Characteristics

Abstract To ensure the coexistence of autonomous personal mobility vehicles (PMVs) and pedestrians in a pedestrian zone, they should be able to smoothly pass across and avoid each other. Studies suggest that it is possible that PMVs and pedestrians can pass each other in a short period of time without compromising their comfort; this can be achieved through understanding how pedestrians react to the behavior of PMVs and by modifying the autonomous navigation of PMVs accordingly. Therefore, in this study, the avoidance behavior characteristics of pedestrians were investigated. Experiments were conducted to understand the influence of the selected avoiding behavior parameters and to understand the behavior characteristics of pedestrians in relation to the behavior of PMVs. Furthermore, a path planning strategy that enables smooth passing was developed based on these characteristics. The usefulness of this method was evaluated. The avoidance time and the avoiding angular velocity at the start and end of the avoidance behavior were the parameters that contributed to smooth autonomous navigation. The results show that pedestrian tolerance improves and the avoidance width decreases depending on these parameters. Furthermore, smooth autonomous navigation can be achieved using the characteristics of pedestrians’ cognition against PMVs.

scholarly journals Autonomous Path Planning Scheme Research for Mobile Robot

2016 ◽  
Vol 16 (4) ◽  
pp. 113-125
Author(s):  
Jianxian Cai ◽  
Xiaogang Ruan ◽  
Pengxuan Li
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Autonomous Navigation ◽  
Learning Algorithm ◽  
Action Learning ◽  
Cognitive Learning ◽  
Learning Ability ◽  
Q Learning ◽  
Planning Strategy ◽  
Navigation Path

Abstract An autonomous path-planning strategy based on Skinner operant conditioning principle and reinforcement learning principle is developed in this paper. The core strategies are the use of tendency cell and cognitive learning cell, which simulate bionic orientation and asymptotic learning ability. Cognitive learning cell is designed on the base of Boltzmann machine and improved Q-Learning algorithm, which executes operant action learning function to approximate the operative part of robot system. The tendency cell adjusts network weights by the use of information entropy to evaluate the function of operate action. The results of the simulation experiment in mobile robot showed that the designed autonomous path-planning strategy lets the robot realize autonomous navigation path planning. The robot learns to select autonomously according to the bionic orientate action and have fast convergence rate and higher adaptability.

Dynamic Path Planning Algorithm Based on Chaos Genetic Vehicle Navigation

2011 ◽  
Vol 142 ◽  
pp. 12-15
Author(s):  
Ping Feng
Keyword(s):  
Path Planning ◽  
Search Algorithm ◽  
Traffic Condition ◽  
Planning Time ◽  
Dynamic Path Planning ◽  
Short Period ◽  
Planning Algorithm ◽  
Dynamic Path ◽  
Path Planning Algorithm ◽  
Chaos Genetic Algorithm

The paper puts forward the dynamic path planning algorithm based on improving chaos genetic algorithm by using genetic algorithms and chaos search algorithm. In the practice of navigation, the algorithm can compute at the best path to meet the needs of the navigation in such a short period of planning time. Furthermore,this algorithm can replan a optimum path of the rest paths after the traffic condition in the sudden.

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 Chaotic Path Planning for 3D Area Coverage Using a Pseudo-Random Bit Generator from a 1D Chaotic Map

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1821
Author(s):  
Lazaros Moysis ◽  
Karthikeyan Rajagopal ◽  
Aleksandra V. Tutueva ◽  
Christos Volos ◽  
Beteley Teka ◽  
...  
Keyword(s):  
Path Planning ◽  
Chaotic Map ◽  
Dynamical Behavior ◽  
Area Coverage ◽  
Phase Portraits ◽  
Planning Strategy ◽  
Spline Curves ◽  
Key Space ◽  
Aerial Vehicle ◽  
Discrete Motion

This work proposes a one-dimensional chaotic map with a simple structure and three parameters. The phase portraits, bifurcation diagrams, and Lyapunov exponent diagrams are first plotted to study the dynamical behavior of the map. It is seen that the map exhibits areas of constant chaos with respect to all parameters. This map is then applied to the problem of pseudo-random bit generation using a simple technique to generate four bits per iteration. It is shown that the algorithm passes all statistical NIST and ENT tests, as well as shows low correlation and an acceptable key space. The generated bitstream is applied to the problem of chaotic path planning, for an autonomous robot or generally an unmanned aerial vehicle (UAV) exploring a given 3D area. The aim is to ensure efficient area coverage, while also maintaining an unpredictable motion. Numerical simulations were performed to evaluate the performance of the path planning strategy, and it is shown that the coverage percentage converges exponentially to 100% as the number of iterations increases. The discrete motion is also adapted to a smooth one through the use of B-Spline curves.

A Path-Planning Strategy for Overhead Cranes With High Hoisting Speed

2002 ◽  
Author(s):  
Ho-Hoon Lee
Keyword(s):  
Path Planning ◽  
High Performance ◽  
Stability Theorem ◽  
Lyapunov Stability Theorem ◽  
Control Laws ◽  
Planning Strategy ◽  
Overhead Cranes ◽  
Time Control ◽  
Small Load ◽  
Load Swing

This paper proposes a path planning strategy for high-performance anti-swing control of overhead cranes, where the anti-swing control problem is solved as a kinematic problem. First, two anti-swing control laws, one for hoisting up and the other for hoisting down, are proposed based on the Lyapunov stability theorem. Then a new path-planning strategy is proposed based on the concept of minimum-time control and the proposed anti-swing control laws. The proposed path planning is free from the usual constraints of small load swing, slow hoisting speed, and small hoisting distance. The effectiveness of the proposed path planning is shown by computer simulation with high hoisting speed and hoisting ratio.

scholarly journals Real-Time Path Planning Based on Harmonic Functions under a Proper Generalized Decomposition-Based Framework

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3943
Author(s):  
Nicolas Montés ◽  
Francisco Chinesta ◽  
Marta C. Mora ◽  
Antonio Falcó ◽  
Lucia Hilario ◽  
...  
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Harmonic Functions ◽  
Autonomous Navigation ◽  
Numerical Technique ◽  
Computational Cost ◽  
Main Idea ◽  
Main Property ◽  
Proper Generalized Decomposition ◽  
Computational Vademecum

This paper presents a real-time global path planning method for mobile robots using harmonic functions, such as the Poisson equation, based on the Proper Generalized Decomposition (PGD) of these functions. The main property of the proposed technique is that the computational cost is negligible in real-time, even if the robot is disturbed or the goal is changed. The main idea of the method is the off-line generation, for a given environment, of the whole set of paths from any start and goal configurations of a mobile robot, namely the computational vademecum, derived from a harmonic potential field in order to use it on-line for decision-making purposes. Up until now, the resolution of the Laplace or Poisson equations has been based on traditional numerical techniques unfeasible for real-time calculation. This drawback has prevented the extensive use of harmonic functions in autonomous navigation, despite their powerful properties. The numerical technique that reverses this situation is the Proper Generalized Decomposition. To demonstrate and validate the properties of the PGD-vademecum in a potential-guided path planning framework, both real and simulated implementations have been developed. Simulated scenarios, such as an L-Shaped corridor and a benchmark bug trap, are used, and a real navigation of a LEGO®MINDSTORMS robot running in static environments with variable start and goal configurations is shown. This device has been selected due to its computational and memory-restricted capabilities, and it is a good example of how its properties could help the development of social robots.

Efficient CNC Tool Path Planning Using Point Cloud

2018 ◽  
Author(s):  
Sumedh Ghogare ◽  
S. S. Pande
Keyword(s):  
Path Planning ◽  
Point Cloud ◽  
Tool Path ◽  
Planning Process ◽  
Cnc Milling ◽  
Tool Path Planning ◽  
Planning Strategy ◽  
Part Quality ◽  
Nc Program ◽  
Cutter Path

This paper reports the development of an efficient iso-scallop tool path planning strategy for machining of freeform surfaces on a three axis CNC milling center using the point cloud as the input. Boundary of the point cloud is chosen as the Master Cutter Path, using which the scallop points are computed. Adjacent side tool paths are computed using these scallop points and the path planning process is completed till the entire surface is covered. The system generates post-processed NC program in ISO format which was extensively tested for various case studies. The results were compared with the iso-planar tool path strategy from commercial software. Our system was found to generate efficient tool path in terms of part quality, productivity and storage memory.

Sign in / Sign up

Export Citation Format

Share Document