Waypoint Tracking Research Articles

Predictive Course Control and Guidance of Autonomous Unmanned Sailboat Based on Efficient Sampled Gaussian Process

In view of the vulnerability of ocean unmanned sailboats to the large lateral velocities due to wind and waves during navigation, this paper proposes a Gaussian Process Model Predictive Control (GPMPC) method based on data-driven learning technique to improve the navigation tracking accuracy of unmanned sailboats. The feature model of the sailing course change subject to the wind and waves is learned from the efficient sampling data. It is then combined with the model predictive control to form the course controller. To reduce the influence of wind and waves disturbances, an adaptive weight term is designed in the object function to improve the tracking accuracy of the model predictive control. The guidance commands received by the model predictive controller take into account the path deviation caused by the current and lateral motion of the ship. The results show that GPMPC has the advantages of fast response time and less overshoot; the unmanned sailboat can better achieve waypoint tracking by learning navigation data.

Modeling, parameter identification, guidance and control of an unmanned surface vehicle with experimental results

This work proposes an autopilot scheme for self-steering an Unmanned Surface Vehicle (USV) in terms of heading and speed control, route following and waypoints tracking.The majority of regulators developed in the literature only provide heading control, which is a considerable weakness since the drift effects due to wind and marine currents cause the USV to move away from the planned path. This work deals with this problem and firstly proposes a mathematical model with three degrees of freedom for simulating the USV behavior. Second, USV parameter are calculated experimentally, and then an autopilot system is designed letting the USV to rapidly and smoothly reach a desired path and remain precisely on it. The developed autopilot, which is based on sliding mode control, consists of two levels of regulation, low-level controller for speed and heading control and a high-level controller for generating the desired speed and heading according to two different navigation modes: waypoints tracking and/or path following.Experimental results are carried out to verify the effectiveness of the proposed autopilot in term of heading control for waypoints tracking.

Design and control of the first foldable single-actuator rotary wing micro aerial vehicle

The monocopter is a type of micro aerial vehicle largely inspired from the flight of botanical samaras (Acer palmatum). A large section of its fuselage forms the single wing where all its useful aerodynamic forces are generated, making it achieve a highly efficient mode of flight. However, compared to a multi-rotor of similar weight, monocopters can be large and cumbersome for transport, mainly due to their large and rigid wing structure. In this work, a monocopter with a foldable, semi-rigid wing is proposed and its resulting flight performance is studied. The wing is non-rigid when not in flight and relies on centrifugal forces to become straightened during flight. The wing construction uses a special technique for its lightweight and semi-rigid design, and together with a purpose-designed autopilot board, the entire craft can be folded into a compact pocketable form factor, decreasing its footprint by 69%. Furthermore, the proposed craft accomplishes a controllable flight in 5 degrees of freedom by using only one thrust unit. It achieves altitude control by regulating the force generated from the thrust unit throughout multiple rotations. Lateral control is achieved by pulsing the thrust unit at specific instances during each cycle of rotation. A closed-loop feedback control is achieved using a motion-captured camera system, where a hybrid proportional stabilizer controller and proportional-integral position controller are applied. Waypoint tracking, trajectory tracking and flight time tests were performed and analyzed. Overall, the vehicle weighs 69 g, achieves a maximum lateral speed of about 2.37 m s−1, an average power draw of 9.78 W and a flight time of 16 min with its semi-rigid wing.

Communication Aware UAV Swarm Surveillance Based on Hierarchical Architecture

Multi-agent unmanned aerial vehicle (UAV) teaming becomes an essential part in science mission, modern warfare surveillance, and disaster rescuing. This paper proposes a decentralized UAV swarm persistent monitoring strategy in realizing continuous sensing coverage and network service. A two-layer (high altitude and low altitude) UAV teaming hierarchical structure is adopted in realizing the accurate object tracking in the area of interest (AOI). By introducing the UAV communication channel model in its path planning, both centralized and decentralized control schemes would be evaluated in the waypoint tracking simulation. The UAV swarm network service and object tracking are measured by metrics of communication link quality and waypoints tracking accuracy. UAV swarm network connectivity are evaluated over different aspects, such as stability and volatility. The comparison of proposed algorithms is presented with simulations. The result shows that the decentralized scheme outperforms the centralized scheme in the mission of persistent surveillance, especially on maintaining the stability of inner UAV swarm network while tracking moving objects.

The Design And Build of Telemetry system Portable Ground Control Station (GCS) as Control and Monitoring on Unmanned Aerial Vehicle (UAV) Aircraft Galak-24

Abstract – Ground Control Station (GCS) is a very important part in controlling and monitoring UAV aircraft as well as monitoring a mission so that operators at the home base can send mission orders. The importance of this mission requires a system in this case, namely the GCS that can be connected to various types of unmanned vehicles. This study develops a GCS system that is used for controlling and monitoring the condition of UAV aircraft and sending waypoint tracking mission commands that are connected to a cloud server via the internet. This system consists of two units, namely the flight unit and the video unit, the flight unit consists of a flight controller, the video unit is a system that is on a camera connected to telemetry and connected to the internet so that it can be accessed via the internet, thus controlling and monitoring UAV aircraft and target control delivery on the GCS will be accessible anywhere via the internet. The GCS system has been able to display the condition of the aircraft status, sending flight hover mission commands, land and sending missions, namely tracking waypoints and camera object coordinates. In areas where the mission's 4G internet signal can run smoothly by sending 15 takeoff and landing control waypoints which manually with precision results, the fix wings type UAV aircraft can pass through several tracking waypoints that experience errors.

A Waypoint Tracking Controller for Autonomous Road Vehicles Using ROS Framework.

Automated Driving Systems (ADSs) require robust and scalable control systems in order to achieve a safe, efficient and comfortable driving experience. Most global planners for autonomous vehicles provide as output a sequence of waypoints to be followed. This paper proposes a modular and scalable waypoint tracking controller for Robot Operating System (ROS)-based autonomous guided vehicles. The proposed controller performs a smooth interpolation of the waypoints and uses optimal control techniques to ensure robust trajectory tracking even at high speeds in urban environments (up to 50 km/h). The delays in the localization system and actuators are compensated in the control loop to stabilize the system. Forward velocity is adapted to path characteristics using a velocity profiler. The controller has been implemented as an ROS package providing scalability and exportability to the system in order to be used with a wide variety of simulators and real vehicles. We show the results of this controller using the novel and hyper realistic CARLA Simulator and carrying out a comparison with other standard and state-of-art trajectory tracking controllers.

Exploration of the applicability of probabilistic inference for learning control in underactuated autonomous underwater vehicles

Underwater vehicles are employed in the exploration of dynamic environments where tuning of a specific controller for each task would be time-consuming and unreliable as the controller depends on calculated mathematical coefficients in idealised conditions. For such a case, learning task from experience can be a useful alternative. This paper explores the capability of probabilistic inference learning to control autonomous underwater vehicles that can be used for different tasks without re-programming the controller. Probabilistic inference learning uses a Gaussian process model of the real vehicle to learn the correct policy with a small number of real field experiments. The use of probabilistic reinforced learning looks for a simple implementation of controllers without the burden of coefficients calculation, controller tuning or system identification. A series of computational simulations were employed to test the applicability of model-based reinforced learning in underwater vehicles. Three simulation scenarios were evaluated: waypoint tracking, depth control and 3D path tracking control. The 3D path tracking is done by coupling together a line-of-sight law with probabilistic inference for learning control. As a comparison study LOS-PILCO algorithm can perform better than a robust LOS-PID. The results shows that probabilistic model based reinforced learning is a possible solution to motion control of underactuated AUVs as can generate capable policies with minimum quantity of episodes.

Study on Control System of Integrated Unmanned Surface Vehicle and Underwater Vehicle.

In this paper, in order to overcome certain limitations of previously commercialized platforms, a new integrated unmanned surface vehicle (USV) and unmanned underwater vehicle (UUV) platform connected via underwater cable capable of acquiring real-time underwater data and long-time operation are studied. A catamaran-type USV was designed to overcome the limitations of an ocean environment and to play the role as the hub of power supply and communication for the integrated platform. Meanwhile, the UUV was designed as torpedo-shaped to minimize hydrodynamic resistance and its hardware design was focused on processing and sending the underwater camera and sonar data. The underwater cable driven by a winch system was installed to supply power from the USV to the UUV and to transmit acquired data form underwater sonar sensor or camera. Different from other previously studied cooperation system of USVs and autonomous underwater vehicles (AUVs), the merit of the proposed system is real-time motion coordination control between the USV and UUV while transmitting large amount of data using the tether cable. The main focus of the study is coordination of the UUV with respect to the global positioning system (GPS) attached at USV and verification of its performance throughout field tests. Waypoint tracking control algorithm was designed and implemented on USV and relative heading, distance control for USV–UUV coordination was implemented to UUV. To ensure the integrity of the coordination control of the integrated platform, a study on accurate measurement system of the relative position between the USV and the UUV by using the GPS and the ultrashort baseline (USBL) device was performed. Individual tests were conducted to verify the performance of USBL and AHRS, which provide the position and heading data of UUV among the sensors mounted on the actual platform, and the effectiveness of the obtained sensor data is presented. Using the accurate measurement system, a number of field tests were conducted to verify the performance of the integrated platform.

Development of an Autonomous Surface Vehicle and Performance Evaluation of Autonomous Navigation Technologies

The use of autonomous marine robots has been rapidly increasing in the development of marine environments. This paper presents the development of an autonomous surface vehicle (ASV) and validation of autonomous navigation technologies. The ASV was developed as a testbed to validate fundamental navigation technologies for autonomous marine robots including both surface and underwater vehicles. The ASV was developed on a catamaran by integrating various sensors and power and electrical propulsion systems, navigation and control systems, and communication devices. As fundamental navigation technologies for ASV, waypoint tracking and obstacle avoidance are developed and tested. Further, using the ASV as a testbed to validate underwater navigation technologies, two types of underwater localization methods were developed. First, an acoustic-based navigation was developed by using acoustic sources as landmarks in underwater environment. The proposed acoustic-based navigation localized both vehicle and source by Kalman filter-based SLAM. Second, terrain-based localization as geophysics-based navigation was developed using a particle filter. Effective resampling can be achieved by using a measurement of terrain roughness. Both acoustic and terrain-based underwater navigation methods are implemented with the developed ASV, and the performance of the navigation methods are evaluated by comparing the estimated localization results to the ground truth acquired by GPS. Several field tests conducted in inland water environments demonstrate the performance of the developed vehicle and navigation algorithms.

Development and Field Test of Unmanned Marine Vehicle (USV/UUV) With cable

This paper presents the system, controller, and field test results of an unmanned marine vehicle (UMV) developed to acquire real-time ocean exploration information. The system consists of an unmanned surface vehicle (USV), an unmanned underwater vehicle (UUV), and an underwater cable. The developed platform is a research platform for ocean exploration and was proposed to compensate for the shortcomings of the existing USV, UUV, and towing system. This paper describes the proposed UMV, including the design considerations such as electronics architecture, data management, sensors, and actuators and explains the path control algorithm and controller used to follow the specified path for ocean exploration. In order to confirm the performance of the developed platform and control algorithm, a way-point tracking experiment was performed, and the results are shown.

Control of stepper motor driven differential drive robot for tracking waypoint trajectories: modeling, simulation, optimization and experimental investigations

ABSTRACT Waypoints are abstract points through which the robot has to be controlled to reach the goal. Waypoint-based robot control can be used as an alternative to continuous trajectory control. This paper discuses the implementation of a waypoint tracking kinematic controller along with a dynamic slip avoidance controller on a stepper motor driven differential drive robot. The dynamic controller utilizes torque limiting strategy to avoid wheel slip that will occur when trajectory tracking is carried out with a kinematic controller alone. Optimization of control parameters is carried out using multi-objective particle swarm optimization technique to minimize trajectory tracking error as well as velocity tracking error. The controller is designed to take care of different velocity constrains on the robot so that it can be employed on a real robot. The controller developed in this work is tested for tracking different waypoint trajectories. The trajectory tracking results are compared with the result of robot control with a kinematic controller. The results show improvement in trajectory tracking, and in velocity tracking.

A Robust Predictive Control Approach for Underwater Robotic Vehicles

This article presents a robust nonlinear model predictive control (NMPC) scheme for autonomous navigation of underwater robotic vehicles operating in a constrained workspace including the static obstacles. In particular, the purpose of the controller is to guide the vehicle toward specific way points with guaranteed input and state constraints. Various constraints, such as obstacles, workspace boundaries, predefined upper bounds for the velocity of the robotic vehicle, and thruster saturations, are considered during the control design. Moreover, the proposed control scheme is designed at dynamic level, and it incorporates the full dynamics of the vehicle in which the ocean currents are also involved. Hence, taking the thrusts as the control inputs of the robotic system and formulating them accordingly, the vehicle exploits the ocean current dynamics when these are in favor of the way-point tracking mission, resulting in reduced energy consumption by the thrusters. The robustness of the closed-loop system against parameter uncertainties has been analytically guaranteed with convergence properties. The performance of the proposed control strategy is experimentally verified using a 4 degrees of freedom (DoF) underwater robotic vehicle inside a constrained test tank with sparse static obstacles.

Successive Waypoints Tracking of an Underactuated Surface Vehicle

In marine guard, patrol, and racing scenarios, it is of great importance to autonomously helm an underactuated surface vehicle (USV) to accurately achieve successive waypoints tracking (SWT) with prescribed velocities and courses. In this paper, in the presence of completely unknown dynamics and environmental forces, the emerging SWT problem is innovatively solved by creating a novel model-free guidance-control integrated framework. In lieu of direct guidance to the waypoint which inevitably suffers from singularity, a new tool called bridge trajectory (BT) exactly passing through the generalized waypoint (GW) is first developed by defining marching and ahead points, i.e., a marching point (MP) and an ahead point (AP). Combining with pursuit guidance and finite-time unknown observer (FUO), successive BTs are switched ON and OFF, with the aid of MP and AP, respectively. By virtue of the FUO, cascade analysis, filtered backstepping, and Lyapunov approach, BT tracking control laws for surge and yaw motions are further synthesized to ensure successive GWs with desired positions, velocities, and courses can be tracked accurately, and thereby eventually contributing to a BT-guided model-free solution to the SWT problem. Simulation studies on a benchmark USV demonstrate remarkable performance of the proposed method.

High precision tracking control for a sequence of way-points using dynamic unicycles

This paper investigates the high precision way-point tracking control problems for dynamic unicycles. Firstly, a simplified electrical motor is used to provide the torques in unicycle’s dynamic model. Then, in order to improve the tracking precision, a kinematic controller and a dynamic controller are proposed to drive the unicycle to its given way-points, respectively. A group of parameter conditions is developed for the tracking system to avoid the singularity. Comparing with the other tracking methods, our proposed tracking controllers can effectively drive the dynamic unicycle to its targets with high precision. The stability and performance of proposed tracking method are strictly analyzed in both kinematic and dynamic levels. In final, numerical simulations are provided to verify the effectiveness and advantages of proposed approaches.

Challenges and implemented technologies used in autonomous drone racing

Autonomous drone racing (ADR) is a challenge for autonomous drones to navigate a cluttered indoor environment without relying on any external sensing in which all the sensing and computing must be done with onboard resources. Although no team could complete the whole racing track so far, most successful teams implemented waypoint tracking methods and robust visual recognition of the gates of distinct colors because the complete environmental information was given to participants before the events. In this paper, we introduce the purpose of ADR as a benchmark testing ground for autonomous drone technologies and analyze challenges and technologies used in the two previous ADRs held in IROS 2016 and IROS 2017. Five teams which participated in these events present their implemented technologies that cover modified ORB-SLAM, robust alignment method for waypoints deployment, sensor fusion for motion estimation, deep learning for gate detection and motion control, and stereo-vision for gate detection.

Experiments on high-performance maneuvers control for a work-class 3000-m remote operated vehicle

The challenge of high-performance maneuvers for a deep-ocean underwater vehicle is to design proper controllers and ensure the high accuracy of vehicle state measurements. Current underwater vehicle control solutions are considered to be a unique controller designed to reject the disturbance and noise. However, the controller is based on a precise hydrodynamic model. It requires multiple underwater experiments and complex theoretical analysis. In this article, a hybrid control strategy is presented for the work-class remote operated vehicle. It tries to compose several proportion–integral–differential controllers into one intelligent sequence in terms of task requirements. The proposed approach employs the iterative learning method to improve the performance of the depth holding and the way-point tracking. A remote operated vehicle system weighted about 1.5 tons is provided as a physical platform for scientific investigations using acoustic Doppler current profiler, inertial navigation system, depth sensor, and an altimeter. Results from the simulation and the experiment in the basin show that the proposed approach provides high accuracy at both conditions: tracking way-points with or without ocean currents and disturbances, which show the effectiveness of the proposed approach. In addition, the thrust vector defined for a propeller facilitates the control of underwater vehicle as the thruster configuration changes.

Switching Control for 3-D Waypoint Tracking of a Biomimetic Underwater Vehicle

This paper addresses the problem of three-dimensional (3-D) waypoint tracking for a biomimetic underwater vehicle (BUV) propelled by undulatory fins: RobCutt-II. Based on the specific mechanical design and control system configuration, the RobCutt-II can perform diversified locomotion patterns, especially submerging or surfacing vertically in the water. For practical underwater operating procedures, a selective switching control for 3-D waypoint tracking is proposed. This control scheme contains a depth controller, a waypoint tracking controller, and a selector. When tracking a series of given 3-D waypoints, the RobCutt-II can switch between two closed-loop locomotion patterns, i.e., the depth control pattern and the waypoint tracking pattern. Simulations and a comparative experimental study demonstrate the feasibility and effectiveness of the proposed switching control scheme.

Control for Dynamic Positioning and Way-point Tracking of Underactuated Autonomous Underwater Vehicles Using Sliding Mode Control

Autonomous Underwater Vehicles (AUVs) are used in many applications such as the exploration of oceans, scientific and military missions, etc. Developing control schemes for AUVs is considered to be a very challenging task due to the complexity of the AUV model, the unmodeled dynamics, the uncertainties and the environmental disturbances. This paper develops a robust control scheme for the dynamic positioning and way-point tracking of underactuated autonomous underwater vehicles. In order to insure the robustness of the proposed controllers, the sliding mode control technique is adopted in the design process. Simulation results are given to validate the proposed controllers. Moreover, studies are presented to evaluate the robustness of the developed controllers with model uncertainties and under different types of disturbances including unknown currents.

Flight Motion Controller Design using Genetic Algorithm for a Quadcopter

In this study, the Genetic Algorithm operability is assigned to optimize the proportional–integral–derivative controller parameters for both simulation and real-time operation of quadcopter flight motion. The optimized proportional–integral–derivative gains, using Genetic Algorithm to minimum the fitness function via the integral of time multiplied by absolute error criterion, are then integrated to control the quadcopter flight motion. In addition, the proposed controller design is successfully implemented to the experimental real-time flight motion. The performance results are proven that the highly effective stability operation and the reliable of waypoint tracking.

Hybrid Locomotion Evaluation for a Novel Amphibious Spherical Robot

We describe the novel, multiply gaited, vectored water-jet, hybrid locomotion-capable, amphibious spherical robot III (termed ASR-III) featuring a wheel-legged, water-jet composite driving system incorporating a lifting and supporting wheel mechanism (LSWM) and mechanical legs with a water-jet thruster. The LSWM allows the ASR-III to support the body and slide flexibly on smooth (flat) terrain. The composite driving system facilitates two on-land locomotion modes (sliding and walking) and underwater locomotion mode with vectored thrusters, improving adaptability to the amphibious environment. Sliding locomotion improves the stability and maneuverability of ASR-III on smooth flat terrain, whereas walking locomotion allows ASR-III to conquer rough terrain. We used both forward and reverse kinematic models to evaluate the walking and sliding gait efficiency. The robot can also realize underwater locomotion with four vectored water-jet thrusters, and is capable of forward motion, heading angle control and depth control. We evaluated LSWM efficiency and the sliding velocities associated with varying extensions of the LSWM. To explore gait stability and mobility, we performed on-land experiments on smooth flat terrain to define the optimal stride length and frequency. We also evaluated the efficacy of waypoint tracking when the sliding gait was employed, using a closed-loop proportional-integral-derivative (PID) control mechanism. Moreover, experiments of forward locomotion, heading angle control and depth control were conducted to verify the underwater performance of ASR-III. Comparison of the previous robot and ASR-III demonstrated the ASR-III had better amphibious motion performance.