Local Path Planning for Autonomous Vehicles Based on the Natural Behavior of the Biological Action-Perception Motion

Bautista-Camino, Pedro; Barranco-Gutiérrez, Alejandro I.; Cervantes, Ilse; Licea, Martín Antonio Rodríguez; Prado-Olivarez, Juan; Pérez-Pinal, Francisco J.

doi:10.3390/en15051769

Cited by 10 publications

(5 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Behavioural planning occurs between the start and finish of the ride. It involves more immediate decisions, such as when to change lanes, selection of safe target velocity in current road conditions and before the upcoming road curves, or navigating through a busy intersection [ 167 , 168 , 169 ]. Behavioural planning works with constraints set by the global plan but reacts to the nearby environment and situations that happen in real time and are predicted for the next moments.…”

Section: Common Controller Layout For Automated Vehiclesmentioning

confidence: 99%

Review of Integrated Chassis Control Techniques for Automated Ground Vehicles

Skrickij,

Kojis,

Šabanovič

et al. 2024

Sensors

View full text Add to dashboard Cite

Integrated chassis control systems represent a significant advancement in the dynamics of ground vehicles, aimed at enhancing overall performance, comfort, handling, and stability. As vehicles transition from internal combustion to electric platforms, integrated chassis control systems have evolved to meet the demands of electrification and automation. This paper analyses the overall control structure of automated vehicles with integrated chassis control systems. Integration of longitudinal, lateral, and vertical systems presents complexities due to the overlapping control regions of various subsystems. The presented methodology includes a comprehensive examination of state-of-the-art technologies, focusing on algorithms to manage control actions and prevent interference between subsystems. The results underscore the importance of control allocation to exploit the additional degrees of freedom offered by over-actuated systems. This paper systematically overviews the various control methods applied in integrated chassis control and path tracking. This includes a detailed examination of perception and decision-making, parameter estimation techniques, reference generation strategies, and the hierarchy of controllers, encompassing high-level, middle-level, and low-level control components. By offering this systematic overview, this paper aims to facilitate a deeper understanding of the diverse control methods employed in automated driving with integrated chassis control, providing insights into their applications, strengths, and limitations.

show abstract

Section: Common Controller Layout For Automated Vehiclesmentioning

confidence: 99%

Review of Integrated Chassis Control Techniques for Automated Ground Vehicles

Skrickij,

Kojis,

Šabanovič

et al. 2024

Sensors

View full text Add to dashboard Cite

show abstract

“…Path planning is a key aspect of UAV operations. Path planning is performed using a behavior-based approach [ 81 ]. This method manages complex environments and makes it easy to design and test behaviors.…”

Section: Bio-inspired Algorithms For Uav Path Planningmentioning

confidence: 99%

Bio-Inspired Optimization-Based Path Planning Algorithms in Unmanned Aerial Vehicles: A Survey

Poudel

Arafat

Moh

2023

Sensors

View full text Add to dashboard Cite

Advancements in electronics and software have enabled the rapid development of unmanned aerial vehicles (UAVs) and UAV-assisted applications. Although the mobility of UAVs allows for flexible deployment of networks, it introduces challenges regarding throughput, delay, cost, and energy. Therefore, path planning is an important aspect of UAV communications. Bio-inspired algorithms rely on the inspiration and principles of the biological evolution of nature to achieve robust survival techniques. However, the issues have many nonlinear constraints, which pose a number of problems such as time restrictions and high dimensionality. Recent trends tend to employ bio-inspired optimization algorithms, which are a potential method for handling difficult optimization problems, to address the issues associated with standard optimization algorithms. Focusing on these points, we investigate various bio-inspired algorithms for UAV path planning over the past decade. To the best of our knowledge, no survey on existing bio-inspired algorithms for UAV path planning has been reported in the literature. In this study, we investigate the prevailing bio-inspired algorithms extensively from the perspective of key features, working principles, advantages, and limitations. Subsequently, path planning algorithms are compared with each other in terms of their major features, characteristics, and performance factors. Furthermore, the challenges and future research trends in UAV path planning are summarized and discussed.

show abstract

“…Many path planning algorithms were initially developed for moving ground robots (e.g. Dijkstra's algorithm [11], the VFH* [12], this algorithm by Bautista et al [13]). Often, these algorithms were extended for UAV operation.…”

Section: Introductionmentioning

confidence: 99%

Obstacle encounter probability dependent local path planner for UAV operation in urban environments

Thoma,

Gardi,

Fisher

et al. 2024

CEAS Aeronaut J

View full text Add to dashboard Cite

Unmanned aerial vehicles (UAVs) are well-suited for various short-distance missions in urban environments. However, the path planner of such UAV is constantly challenged with the choice between avoiding obstacles horizontally or vertically. If the path planner relies on sensor information only, i.e. the path planner is a local planner, usually predefined manoeuvres or preferences are used to find a possible way. However, this method is stiff and inflexible. This work proposes a probabilistic decision-maker to set the control parameters of a classic local path planner during a flight mission. The decision-maker defines whether performing horizontal or vertical avoidance is preferable based on the probability of encountering a given number of obstacles. Here, the decision-maker considers predictions of possible future avoidance manoeuvres. It also defines an ideal flight altitude based on the probability of encountering obstacles. This work analyses the building height of all European capital cities and the probability of encountering obstacles at different altitudes to feed the decision-maker. We tested the feasibility of the proposed decision-maker with the 3DVFH*, a commonly used local path planner, in multiple simulations. The proposed probabilistic decision-maker allows the local path planner to reach the goal point significantly more often than the standard version of the 3DVFH*.

show abstract

Local Path Planning for Autonomous Vehicles Based on the Natural Behavior of the Biological Action-Perception Motion

Cited by 10 publications

References 53 publications

Review of Integrated Chassis Control Techniques for Automated Ground Vehicles

Review of Integrated Chassis Control Techniques for Automated Ground Vehicles

Bio-Inspired Optimization-Based Path Planning Algorithms in Unmanned Aerial Vehicles: A Survey

Obstacle encounter probability dependent local path planner for UAV operation in urban environments

Contact Info

Product

Resources

About