Speed control of DC motors is essential for automated vehicles and four-wheel differential drive (4WD) cars, which are distinct by their high level of maneuverability. The PID controller is one of the most popular techniques for controlling speed, but tuning its parameters is challenging. This paper presents a novel hybrid algorithm, the Moth-Flame Particle Swarm Optimization...
To improve the vertical plane motion performance of an underwater vehicle with bow and stern elevators under actuator saturation and external disturbance conditions, a new control method is proposed in this paper. Firstly, for simplifying the analysis of the coupled kinetics equation of the underwater vehicle, virtual control variables are introduced to decompose the kinetics...
Simultaneous Localization and Mapping (SLAM) is a cornerstone capability for intelligent mobile robots, enabling them to accurately estimate their positions in unknown environments. However, most of the state-of-the-art visual SLAM systems rely on the assumption of static scenes, leading to significantly reduced accuracy and robustness in dynamic environments. In this paper, a...
Compact robots operating beneath the crop canopy present great potential for a range of autonomous and remote tasks, including phenotyping, soil analysis, and cover cropping. Under-canopy navigation presents unique challenges, such as the need for a navigation system that can traverse diverse crop types, navigate despite sensory obstructions, and manage sensory noise effectively...
In recent years, Reinforcement Learning (RL) has made promising progress in several areas, such as control tasks and video games, by using simple, low-dimensional data. However, it struggles when it needs to process more complex, high-dimensional inputs like raw pixel images, offering results that are not as good as those that use information from laser sensors, as many robotics...
Robots following humans is an efficient and practical feature, particularly in the context of service robotics. However, the majority of existing research has focused on the robot following the human from behind, with relatively little attention given to the robot operating in front of the human. This following-in-front approach, where the robot remains within the user’s field of...
This article introduces a novel Multi-agent path planning scheme based on Conflict Based Search (CBS) for heterogeneous holonomic and non-holonomic agents, designated as Heterogeneous CBS (HCBS). The proposed methodology employs a hybrid $$A^*$$ algorithm for non-holonomic car-like robots and a conventional $$A^*$$ algorithm for holonomic robots. Following this, a body conflict...
Recent advancements in lower limb exoskeleton control have predominantly focused on enhancing walking capabilities across diverse terrains, such as level ground, stairs, and ramps. However, achieving seamless transitions between these terrains remains a significant challenge due to the unpredictability of the environment, which hampers adaptive control. In this paper, we propose...
The advent of mass customization has precipitated a need within the industry for the implementation of collaborative robots, which facilitate the integration of human cognitive capabilities with the speed and repeatability of robots. This coupling, however, engenders a closer collaboration between the partners, thereby necessitating collective synergy to achieve optimal...
Ground transportation in dense urban environments has been facing challenges for many years (e.g., congestion and resilience) and the problem of congestion in urban environments will become more significant with the growth of populations and urbanization. In the past few years, the industry and the scientific communities have invested resources towards creating new ideas to...
To intercept a maneuvering target with a predetermined impact angle, a computational intelligence guidance law was proposed in this paper. Based on the theory of two-player zero-sum differential games, this problem is resolved efficiently by solving the Hamilton–Jacobi–Isaacs (HJI) equation. The Nash equilibrium solution of HJI equation can be solved with a policy iteration (PI...
Hybrid aerial underwater vehicles (HAUVs) can operate in water and air and are qualified for complex missions on the air-water interfaces. The unique working conditions put forward higher requirements for the propulsion systems of the vehicles. Present HAUVs’ propulsion systems mostly use propellers, but normal aerial propellers work inefficiently underwater, constraining the...
Recent advancements in Multi-Robot Systems (MRS) and mesh network technologies pave the way for innovative approaches to explore extreme environments. The Artemis Accords, a series of international agreements, have further catalyzed this progress by fostering cooperation in space exploration, emphasizing the use of cutting-edge technologies. In parallel, companies across various...
During the past few years, there has been a rise in novel fully actuated multirotor UAV configurations, each customised to perform a different task. These configurations must be optimised to extract their full potential for the different use cases. The main issue with existing optimisation methods is the computational cost required to produce a design when the optimisation...
Considering the contact between robot feet and the ground is unpredictable in unstructured terrains, robots require fast and accurate contact detection capability. This paper presents a contact detection method through estimating external force that benefits from compensating friction torque and driving torque effectively. For estimating external force, a new estimation method...
Cooperative manipulators face challenges related to an inadequate distribution of external loads and a decrease in Dynamic Load Carrying Capacity (DLCC). Understanding the impact of optimal load distribution on power consumption, load carrying capacity, and gripper error is crucial. This paper presents the Intelligent Saturation Power Limit Load Distribution Algorithm (ISPLLDA...
This paper addresses the problem of performing aggressive manoeuvres by using multirotor vehicles that include passing through any specific point within the full state space of the vehicle. To this end, the design of optimal trajectories considers the dynamical model of the vehicles by numerically integrating it backwards in time, in the manifold where the dynamics evolve, and...
In this paper, we propose a novel loop closure detection algorithm that uses graph attention neural networks to encode semantic graphs to perform place recognition and then use semantic registration to estimate the 6 DoF relative pose constraint. Our place recognition algorithm has two key modules, namely, a semantic graph encoder module and a graph comparison module. The...
Rapidly Exploring Random Tree (RRT) algorithms, notably used for nonholonomic vehicle navigation in complex environments, are often not thoroughly evaluated for their specific challenges. This paper presents a first such comparison study of the variants Potential-Quick RRT* (PQ-RRT*), Informed RRT* (IRRT*), RRT*, and RRT, in maritime single-query nonholonomic motion planning...
Unmanned Aerial Vehicles (UAVs), adept at aerial surveillance, are often constrained by their limited battery capacity. Refueling on slow-moving Unmanned Ground Vehicles (UGVs) can significantly enhance UAVs’ operational endurance. This paper explores the computationally complex problem of cooperative UAV-UGV routing for vast area surveillance, considering speed and fuel...
The performance of visual SLAM systems, in terms of both robustness and accuracy, can be affected by the presence of dynamic objects in dynamic environments. The utilization of learning-based dynamic SLAM algorithms introduces additional challenges, such as increased power consumption and computing requirements, particularly on mobile platforms. Millimeter wave radar has the...
This paper investigates the problem of adaptive tracking control for a class of uncertain multi-input and multi-output nonlinear systems in the presence of asymmetric input constraints and external disturbance. In order to address the different action ranges of input signals in asymmetric dead-zone and saturation models, an adaptive backstepping control method related to...
In this review, the optimal control designs via adaptive dynamic programming (ADP) of unmanned vehicles are investigated. Various complex tasks in unmanned systems are addressed as fundamental optimal regulation and tracking control problems related to the position and attitude of vehicles. The optimal control can be obtained by solving the Hamilton-Jacobi-Bellman equation using...
This paper presents a practical and automated system for high-accuracy drone detection and classification using acoustic signals. Our approach leverages a novel frequency feature extraction method based on the Prony algorithm, which enables efficient detection and classification of drones. To assess the effectiveness of our proposed method, we conducted experiments on a new...
Multi-Agent Reinforcement Learning (MARL) promises to address the challenges of cooperation and competition among multiple agents, often involving safety-critical scenarios. However, realizing safe MARL remains a domain of limited progress. Current works extend single-agent safe learning approaches, employing shielding or backup policies to ensure safety satisfaction...