Optimal Trajectory Design for Conflict Resolution and Collision Avoidance of Flying Robots using Radau-Pseudo Spectral Approach

Kosari, Amirreza; Teshnizi, Masoud Mirzaei

doi:10.1109/icrom.2018.8657506

Cited by 5 publications

(6 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A method for trajectory planning of multiple flying robots in decentralized manner is presented by (A. Kosari and M. M. Teshnizi, 2018) .A method for collision avoidance in line follower multiple robots by using IR sensors is presented by (M. M. Almasri et al, 2016;V. Singhal et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

An orchestrator for networked control systems and its application to collision avoidance in multiple mobile robots

Jain

Ibeke

Agrawal³

2021

IJESMS

View full text Add to dashboard Cite

Networked Control System (NCS) consists of controlled distributed nodes while an Orchestrator functions as a central coordinator for controlling the distributed tasks. The NCSs have challenges of coordination and right execution sequencing of operations. This paper proposes a framework named Controlled Orchestrator (COrch) for coordinating and sequencing the tasks of NCSs. An experiment was performed with three robotic vehicles that are considered as individual control system. Furthermore, the proposed orchestrator COrch decided the sequencing of operations of the robots while performing obstacle avoidance task for spatially distributed robots in parallel. COrch is used to control this task by utilizing the concept of Remote Method Invocation (RMI) and multithreading. RMI is used to prepare the software for controlling the robots at remote end while multithreading is used to perform parallel and synchronize execution of multiple robots. The remote end software generates signals for sequential ,parallel and hybrid mode execution.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

An orchestrator for networked control systems and its application to collision avoidance in multiple mobile robots

Jain

Ibeke

Agrawal³

2021

IJESMS

View full text Add to dashboard Cite

show abstract

“…Unfortunately, many force field methods, like the optimized path planning-based approach of the 3D vector field histogram [27] are predominantly suited for rotary-wing UAVs and may not translate well to fixed-wing UAV scenarios. While path planning-based methods offer high accuracy, some of them, like combining differential game problems with tree-based path planning [28], utilizing reinforcement learning for UAV guidance [29], optimizing flight trajectory with a bank-turn mechanism [30], employing the Radau-pseudospectral approach [31], applying probabilistic methods in collision detection [32], or generating an automated distributed policy for multi-robot motion planning [33], may face significant computational challenges when implemented in real time for small UAVs. Analytical formulations such as the speed approach [34] and the use of buffered Voronoi Cells for path planning [35], though computationally efficient, may lack intuitive understanding and require specialized expertise to implement effectively.…”

Section: Introductionmentioning

confidence: 99%

Genetic Fuzzy Inference System-Based Three-Dimensional Resolution Algorithm for Collision Avoidance of Fixed-Wing UAVs

Rauniyar,

Kim

2023

Electronics

View full text Add to dashboard Cite

Fixed-wing Unmanned Aerial Vehicles (UAVs) cannot fly at speeds lower than critical stall speeds. As a result, hovering during a potential collision scenario, like with rotary-wing UAVs, is impossible. Moreover, hovering is not an optimal solution for Collision Avoidance (CA), as it increases mission time and is innately fuel-inefficient. This work proposes a decentralized Fuzzy Inference System (FIS)-based resolution algorithm that modulates the point-to-point mission path while ensuring the continuous motion of UAVs during CA. A simplified kinematic guidance model with coordinated turn conditions is considered to control the UAVs. The model employs a proportional-derivative control of commanded airspeed, bank angle, and flight path angle. The commands are derived from the desired path, characterized by airspeed, heading, and altitude. The desired path is, in turn, obtained using look-ahead points generated for the target point. The FIS aims to mimic human behavior during collision scenarios, generating modulation parameters for the desired path to achieve CA. Notably, it is also scalable, which makes it easy to adjust the algorithm parameters, as per the required missions, and factors specific to a given UAV. A genetic algorithm was used to optimize FIS parameters so that the distance traveled during the mission was minimized despite path modulation. The proposed algorithm was optimized using a pairwise conflict scenario. The effectiveness of the algorithm was evaluated through a Monte Carlo simulation of random conflict scenarios involving multiple UAVs operating in a confined space.

show abstract

“…It uses the idea of optimal control to transfer the collision avoidance problem into a collision-free trajectory planning problem. [18][19][20][21] This kind of methods can yield an optimal result but require a large amount of calculation. Many different optimization algorithms, such as mixed integer linear programming (MILP), [22][23][24] sequential convex programming (SCP), 25,26 rolling optimization algorithm, and model predictive control (MPC), [27][28][29] have been applied to effectively reduce the computational complexity of the method.…”

Section: Introductionmentioning

confidence: 99%

Trajectory planning with mid-air collision avoidance for quadrotor unmanned aerial vehicles

Jiang

Damaren

2021

Proceedings of the Institution of Mechanical Engineers, Part G:

View full text Add to dashboard Cite

Flight collision between unmanned aerial vehicles (UAVs) in mid-air poses a potential risk to flight safety in low-altitude airspace. This article transforms the problem of collision avoidance between quadrotor UAVs into a trajectory-planning problem using optimal control algorithms, therefore achieving both robustness and efficiency. Specifically, the pseudospectral method is introduced to solve the raised optimal control problem, while the generated optimal trajectory is precisely followed by a feedback controller. It is worth noting that the contributions of this article also include the introduction of the normalized relative coordinate, so that UAVs can obtain collision-free trajectories more conveniently in real time. The collision-free trajectories for a classical scenario of collision avoidance between two UAVs are given in the simulation part by both solving the optimal control problem and querying the prior results. The scalability of the proposed method is also verified in the simulation part by solving a collision avoidance problem among multiple UAVs.

show abstract

Optimal Trajectory Design for Conflict Resolution and Collision Avoidance of Flying Robots using Radau-Pseudo Spectral Approach

Cited by 5 publications

References 25 publications

An orchestrator for networked control systems and its application to collision avoidance in multiple mobile robots

An orchestrator for networked control systems and its application to collision avoidance in multiple mobile robots

Genetic Fuzzy Inference System-Based Three-Dimensional Resolution Algorithm for Collision Avoidance of Fixed-Wing UAVs

Trajectory planning with mid-air collision avoidance for quadrotor unmanned aerial vehicles

Contact Info

Product

Resources

About