scholarly journals Simulated Sensor Based Strategies for Obstacle Avoidance Using Velocity Profiling for Autonomous Vehicle FURBOT

Electronics ◽  
2020 ◽  
Vol 9 (6) ◽  
pp. 883 ◽  
Author(s):  
Khayyam Masood ◽  
Rezia Molfino ◽  
Matteo Zoppi
Keyword(s):  
Mathematical Model ◽  
Velocity Profile ◽  
Obstacle Avoidance ◽  
Autonomous Vehicle ◽  
Velocity Control ◽  
Steering Control ◽  
Traffic Lights ◽  
Simulated Environment ◽  
Last Mile ◽  
Robotic Vehicle

Freight Urban Robotic Vehicle (FURBOT) is an autonomous vehicle designed to transport last mile freight to designated urban stations. It is a slow vehicle designed to tackle urban environment with complete autonomy. A slow vehicle may have slightly different strategies for avoiding obstacles. Unlike on a highway, it has to deal with pedestrians, traffic lights and slower vehicles while maintaining smoothness in its drive. To tackle obstacle avoidance for this vehicle, sensor feedback based strategies have been formulated for smooth drive and obstacle avoidance. A full mathematical model for the vehicle is formulated and simulated in MATLAB environment. The mathematical model uses velocity control for obstacle avoidance without steering control. The obstacle avoidance is attained through velocity control and strategies are formulated with velocity profiling. Innovative techniques are formulated in creating the simulated sensory feed-backs of the environment. Using these feed-backs, correct velocity profiling is autonomously created for giving velocity profile input to the velocity controller. Proximity measurements are assumed to be available for the vehicle in its given range of drive. Novelty is attained by manipulating velocity profile without prior knowledge of the environment. Four different type of obstacles are modeled for simulated environment of the vehicle. These obstacles are randomly placed in the path of the vehicle and autonomous velocity profiling is verified in simulated environment. The simulated results obtained show satisfactory velocity profiling for controller input. The current technique helps to tune the existing controller and in designing of a better velocity controller for the autonomous vehicle and bridges the gap between sensor feed-back and controller input. Moreover, accurate input profiling creates less strain on the system and brings smoothness in drive for an overall safer environment.

Velocity Control of a Cylindrical Rolling Robot by Surface-Morphing

2015 ◽  
Author(s):  
Michael Puopolo ◽  
J. D. Jacob
Keyword(s):  
Mathematical Model ◽  
Angular Velocity ◽  
Velocity Profile ◽  
Average Velocity ◽  
Equations Of Motion ◽  
Angular Position ◽  
Velocity Control ◽  
Control Scheme ◽  
Rolling Robot ◽  
Angular Velocity Profile

A mathematical model is developed for a rolling robot with a cylindrically-shaped, elliptical outer surface that has the ability to alter its shape as it rolls, resulting in a torque imbalance that accelerates or decelerates the robot. A control scheme is implemented, whereby angular position and angular velocity are used as feedback to trigger and define morphing actuation. The goal of the control is to direct the robot to follow a given angular velocity profile. Equations of motion for the rolling robot are formulated and solved numerically. Results show that by automatically morphing its shape in a periodic fashion, the rolling robot is able to start from rest, achieve constant average velocity and slow itself in order to follow a desired velocity profile with significant accuracy.

Obstacle Avoidance in Simulated Environment Using Eye Tracking Technologies

2009 ◽  
Author(s):  
Csaba Antonya ◽  
Florin Barbuceanu ◽  
Zolta´n Rusa´k ◽  
Doru Talaba ◽  
Silviu Butnariu ◽  
...  
Keyword(s):  
Eye Movements ◽  
Obstacle Avoidance ◽  
Autonomous Vehicle ◽  
Computer Game ◽  
Gaze Fixation ◽  
The Gaze ◽  
Simulated Environment ◽  
Mapping System ◽  
Avoidance Strategies ◽  
Human Eye Movements

The paper is investigating the relationship between human eye movements, correlated with the visual perception of computer generated scene on one hand and obstacle avoidance strategies on the other hand, during the process of driving a computer game-like car. Several issues were investigated regarding how the gaze fixation point of the driver is moving during obstacle avoidance maneuvers. The relevance of each issue in making a decision was assessed. The main goal is to establish a correlation (mapping) system between gaze fixation parameters and obstacles avoidance strategies in order to be able to develop cognitive algorithms for driver assistance in real world driving conditions, to monitor driver’s vigilance and ultimately to enable progress towards the autonomous vehicle which can avoid possible obstacles or resolve hazardous traffic situations just by monitoring the eye movements of the driver.

scholarly journals Development of an Improved Rapidly Exploring Random Trees Algorithm for Static Obstacle Avoidance in Autonomous Vehicles

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2244
Author(s):  
S. M. Yang ◽  
Y. A. Lin
Keyword(s):  
Path Planning ◽  
Obstacle Avoidance ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Optimal Path ◽  
Random Trees ◽  
Average Deviation ◽  
Lane Changes ◽  
Path Smoothing ◽  
Rapidly Exploring Random Trees

Safe path planning for obstacle avoidance in autonomous vehicles has been developed. Based on the Rapidly Exploring Random Trees (RRT) algorithm, an improved algorithm integrating path pruning, smoothing, and optimization with geometric collision detection is shown to improve planning efficiency. Path pruning, a prerequisite to path smoothing, is performed to remove the redundant points generated by the random trees for a new path, without colliding with the obstacles. Path smoothing is performed to modify the path so that it becomes continuously differentiable with curvature implementable by the vehicle. Optimization is performed to select a “near”-optimal path of the shortest distance among the feasible paths for motion efficiency. In the experimental verification, both a pure pursuit steering controller and a proportional–integral speed controller are applied to keep an autonomous vehicle tracking the planned path predicted by the improved RRT algorithm. It is shown that the vehicle can successfully track the path efficiently and reach the destination safely, with an average tracking control deviation of 5.2% of the vehicle width. The path planning is also applied to lane changes, and the average deviation from the lane during and after lane changes remains within 8.3% of the vehicle width.

Proportional Navigation and Model Predictive Control of an Unmanned Autonomous Vehicle for Obstacle Avoidance

2018 ◽  
Author(s):  
Ryan P. Shaw ◽  
David M. Bevly
Keyword(s):  
Obstacle Avoidance ◽  
Autonomous Vehicle ◽  
Integrated System ◽  
Reference Trajectory ◽  
Ground Vehicles ◽  
Proportional Navigation ◽  
Predictive Controller ◽  
Proportional Navigation Law ◽  
Vehicle Dynamic Model ◽  
And Control

This paper presents a new approach for the guidance and control of a UGV (Unmanned Ground Vehicle). An obstacle avoidance algorithm was developed using an integrated system involving proportional navigation (PN) and a nonlinear model predictive controller (NMPC). An obstacle avoidance variant of the classical proportional navigation law generates command lateral accelerations to avoid obstacles, while the NMPC is used to track the reference trajectory given by the PN. The NMPC utilizes a lateral vehicle dynamic model. Obstacle avoidance has become a popular area of research for both unmanned aerial vehicles and unmanned ground vehicles. In this application an obstacle avoidance algorithm can take over the control of a vehicle until the obstacle is no longer a threat. The performance of the obstacle avoidance algorithm is evaluated through simulation. Simulation results show a promising approach to conditionally implemented obstacle avoidance.

scholarly journals The Research on the Visual Obstacle-Avoidance Optimization in Robots Control

2013 ◽  
Vol 756-759 ◽  
pp. 372-375
Author(s):  
Hong Bin Tian
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Obstacle Avoidance ◽  
Visual Information ◽  
Structural Model ◽  
Three Dimension ◽  
Coordination Control ◽  
Dimension Space ◽  
The Mathematical Model ◽  
Very High

In order to increase the movement capability of the robotic visual system in three-dimension space, the paper designs an obstacle-avoidance algorithm based on robotic movement visual by effectively processing the visual information colleted by the robotics. This paper establishes a structural model of coordination control system. The obstacles can be effectively identified and avoided by the obstacle-avoidance theory in the robotics coordination operation. The mathematical model of the obstacle-avoidance algorithm can predict the locations of the obstacles. The experiment proves the proposed algorithm can avoid the obstacles in three-dimension space and the accuracy is very high.

scholarly journals Real - Time Trajectory and Velocity Planning for Autonomous Vehicles

2021 ◽  
Vol 10 (5) ◽  
pp. 439-448
Author(s):  
Hrishikesh Dey ◽  
Rithika Ranadive ◽  
Abhishek Chaudhari
Keyword(s):  
Path Planning ◽  
Velocity Profile ◽  
Real Time ◽  
Autonomous Vehicle ◽  
Optimal Path ◽  
Autonomous Driving ◽  
Navigation Algorithm ◽  
Velocity Planning ◽  
Planning Algorithm ◽  
Path Planner

Path planning algorithm integrated with a velocity profile generation-based navigation system is one of the most important aspects of an autonomous driving system. In this paper, a real-time path planning solution to obtain a feasible and collision-free trajectory is proposed for navigating an autonomous car on a virtual highway. This is achieved by designing the navigation algorithm to incorporate a path planner for finding the optimal path, and a velocity planning algorithm for ensuring a safe and comfortable motion along the obtained path. The navigation algorithm was validated on the Unity 3D Highway-Simulated Environment for practical driving while maintaining velocity and acceleration constraints. The autonomous vehicle drives at the maximum specified velocity until interrupted by vehicular traffic, whereas then, the path planner, based on the various constraints provided by the simulator using µWebSockets, decides to either decelerate the vehicle or shift to a more secure lane. Subsequently, a splinebased trajectory generation for this path results in continuous and smooth trajectories. The velocity planner employs an analytical method based on trapezoidal velocity profile to generate velocities for the vehicle traveling along the precomputed path. To provide smooth control, an s-like trapezoidal profile is considered that uses a cubic spline for generating velocities for the ramp-up and ramp-down portions of the curve. The acceleration and velocity constraints, which are derived from road limitations and physical systems, are explicitly considered. Depending upon these constraints and higher module requirements (e.g., maintaining velocity, and stopping), an appropriate segment of the velocity profile is deployed. The motion profiles for all the use-cases are generated and verified graphically.

scholarly journals Data-Driven Analysis of Bicycle Sharing Systems as Public Transport Systems Based on a Trip Index Classification

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4315
Author(s):  
Mark Richard Wilby ◽  
Juan José Vinagre Díaz ◽  
Rubén Fernández Pozo ◽  
Ana Belén Rodríguez González ◽  
José Manuel Vassallo ◽  
...  
Keyword(s):  
Transport System ◽  
Public Transport ◽  
Transport Systems ◽  
Mathematical Framework ◽  
The Public ◽  
Traffic Lights ◽  
Public Transport System ◽  
Specific Analysis ◽  
Last Mile

Bicycle Sharing Systems (BSSs) are exponentially increasing in the urban mobility sector. They are traditionally conceived as a last-mile complement to the public transport system. In this paper, we demonstrate that BSSs can be seen as a public transport system in their own right. To do so, we build a mathematical framework for the classification of BSS trips. Using trajectory information, we create the trip index, which characterizes the intrinsic purpose of the use of BSS as transport or leisure. The construction of the trip index required a specific analysis of the BSS shortest path, which cannot be directly calculated from the topology of the network given that cyclists can find shortcuts through traffic lights, pedestrian crossings, etc. to reduce the overall traveled distance. Adding a layer of complication to the problem, these shortcuts have a non-trivial existence in terms of being intermittent, or short lived. We applied the proposed methodology to empirical data from BiciMAD, the public BSS in Madrid (Spain). The obtained results show that the trip index correctly determines transport and leisure categories, which exhibit distinct statistical and operational features. Finally, we inferred the underlying BSS public transport network and show the fundamental trajectories traveled by users. Based on this analysis, we conclude that 90.60% of BiciMAD’s use fall in the category of transport, which demonstrates our first statement.

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