scholarly journals Guidance-Based Motion Planning of Autonomous Systems

2020 ◽  
Author(s):  
Bülent Özkan

Motion planning is a significant stage in the control of autonomous systems. As an alternative method, guidance approach is proposed for the motion planning of those systems. In guided munitions, guidance laws determine the success of the guidance systems designed to steer systems such as missiles and guided bombs towards predefined targets. The guidance laws designated according to determinative agents such as the firing position of the munition, target type, and operational requirements try to provide the munition with arriving at the target point even under the disturbing effects. In this study, the applicability of the guidance laws to autonomous systems is investigated in a manner similar to the approach for the guided munitions. For this purpose, the motion planning of the selected robotic arm, tracked land vehicle, and quadrotor is tried to be performed in order to move them to predefined target points. Having designed the control systems compatible to the selected guidance laws for the considered systems, the corresponding guidance scheme is constructed. Eventually, after conducting the relevant computer simulations, it is observed that the desired target chase can be made in a successive manner for all cases.

2021 ◽  
Vol 18 (4) ◽  
pp. 172988142110192
Author(s):  
Ben Zhang ◽  
Denglin Zhu

Innovative applications in rapidly evolving domains such as robotic navigation and autonomous (driverless) vehicles rely on motion planning systems that meet the shortest path and obstacle avoidance requirements. This article proposes a novel path planning algorithm based on jump point search and Bezier curves. The proposed algorithm consists of two main steps. In the front end, the improved heuristic function based on distance and direction is used to reduce the cost, and the redundant turning points are trimmed. In the back end, a novel trajectory generation method based on Bezier curves and a straight line is proposed. Our experimental results indicate that the proposed algorithm provides a complete motion planning solution from the front end to the back end, which can realize an optimal trajectory from the initial point to the target point used for robot navigation.


Author(s):  
Mark W. Mueller ◽  
Seung Jae Lee ◽  
Raffaello D’Andrea

The design and control of drones remain areas of active research, and here we review recent progress in this field. In this article, we discuss the design objectives and related physical scaling laws, focusing on energy consumption, agility and speed, and survivability and robustness. We divide the control of such vehicles into low-level stabilization and higher-level planning such as motion planning, and we argue that a highly relevant problem is the integration of sensing with control and planning. Lastly, we describe some vehicle morphologies and the trade-offs that they represent. We specifically compare multicopters with winged designs and consider the effects of multivehicle teams. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.


Author(s):  
Henrik Sandberg ◽  
Vijay Gupta ◽  
Karl H. Johansson

Cyber-vulnerabilities are being exploited in a growing number of control systems. As many of these systems form the backbone of critical infrastructure and are becoming more automated and interconnected, it is of the utmost importance to develop methods that allow system designers and operators to do risk analysis and develop mitigation strategies. Over the last decade, great advances have been made in the control systems community to better understand cyber-threats and their potential impact. This article provides an overview of recent literature on secure networked control systems. Motivated by recent cyberattacks on the power grid, connected road vehicles, and process industries, a system model is introduced that covers many of the existing research studies on control system vulnerabilities. An attack space is introduced that illustrates how adversarial resources are allocated in some common attacks. The main part of the article describes three types of attacks: false data injection, replay, and denial-of-service attacks. Representative models and mathematical formulations of these attacks are given along with some proposed mitigation strategies. The focus is on linear discrete-time plant models, but various extensions are presented in the final section, which also mentions some interesting research problems for future work. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.


10.29007/1kq2 ◽  
2018 ◽  
Author(s):  
Chuchu Fan ◽  
Parasara Sridhar Duggirala ◽  
Sayan Mitra ◽  
Mahesh Viswanathan

In this paper, we present the progress we have made in verifying the benchmark powertrain control systems introduced in the last ARCH workshop. We implemented the algorithm for computing local discrepancy (rate of convergence or divergence of trajectories) reported in the hybrid system verification tool C2E2. We created Stateflow translations of the original models to aid the processing using C2E2 tool. We also had to encode the different driver behaviors in the form of state machines. With these customizations, we have been successful in verifying one of the easier (but still challenging) benchmarks from the powertrain suite. In this paper, we present some of the engineering challenges and describe the artifacts we created in the process.


2019 ◽  
Vol 16 (04) ◽  
pp. 1950012 ◽  
Author(s):  
Mircea Hulea ◽  
Adrian Burlacu ◽  
Constantin-Florin Caruntu

This paper details an intelligent motion planning and control approach for a one-degree of freedom joint of a robotic arm that can be used to implement anthropomorphic robotic hands. This intelligent control method is based on bio-inspired electronic neural networks and contractile artificial muscles implemented with shape memory alloy (SMA) actuators. The spiking neural network (SNN) includes several excitatory neurons that naturally determine the contraction force of the actuators, and unevenly distributed inhibitory neurons that regulate the excitatory activity. To validate the proposed concept, the experiments highlight the motion planning and control of a single-joint robotic arm. The results show that the electronic neural network is able to intelligently activate motion and hold with high precision the mobile link to the target positions even if the arm is slightly loaded. These results are encouraging for the development of improved biologically plausible neural structures that are able to control simultaneously multiple muscles.


Author(s):  
G Wronski ◽  
R G Wilson

The bulk of the electricity generated within the Central Electricity Generating Board (CEGB) is produced from units with a capacity of 500 MW and above. A further 10.2 GW of generation is due to be commissioned in the next few years. Hence those 500 MW units with the highest generating costs now need to develop a flexible operating capability. An attempt is made to define the effect on plant performance of improving the plant automatic controls systems and enhancing the amount and presentation of information to operating staff. The consequences on plant performance of providing minute to minute regulation against grid frequency are given. The economic consequences of running at off design conditions are evaluated and related to the benefits of modernizing the control and display systems on the 500 MW units. Examples are given of the improvements being made in instrumentation and data handling systems.


1994 ◽  
Vol 47 (2) ◽  
pp. 236-258 ◽  
Author(s):  
N. A. J. Witt ◽  
R. Sutton ◽  
K. M. Miller

Over the past seventy years many advances have been made in the field of ship control. Early developments by Sperry and Minorsky on proportional controllers have led to today's modern control systems which have interfacing capabilities with position fixing equipment.This paper presents a brief historical summary of the methods employed in ship control from early proportional devices through the range of adaptive systems and concludes with details of a possible future control method known as intelligent control.Intelligent control consists of three methodologies: expert, fuzzy and neural. An investigation and comparison of the methodologies will present possible future control strategies.


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