Towards terrain-aided navigation for underwater robotics

This paper describes an approach to autonomous navigation for an undersea vehicle that uses information from a scanning sonar to generate navigation estimates based on a simultaneous localization and mapping algorithm. Development of low-speed platform models for vehicle control and the theoretical and practical details of mapping and position estimation using sonar are provided. An implementation of these techniques on a small submersible vehicle 'Oberon' are presented.     

Autonomous Navigation of an Unmanned Air Vehicle Towards a Moving Ship

This paper deals with the problem of autonomous navigation of an unmanned air vehicle towards a moving ship. The ship is moving in the horizontal plane; however, its motion is not a priori known to the air vehicle. The control laws for the flight path angle and the heading angle of the air vehicle are based on the relative kinematics equations between the vehicle and the moving ship. The goal of the control law is to drive the vertical line of sight angle to zero, while the horizontal line of sight angle tracks the heading angle of the ship. This results in a decreasing range in both the horizontal and vertical planes. The kinematics equations under the control law are derived and our results are rigorously proven. Simulation of various scenarios is carried out.     

Mobile robot tracking of pre-planned paths

A method of mobile robot steering control around pre-planned paths is presented. The system can maneuver accurately at low speeds by deriving control parameters as functions of vehicle velocity. The peak demand on the steering controller is reduced, by distributing steering curvature changes evenly over the extent of a maneuver.     

A micro-rover navigation and control system for autonomous planetary exploration

This paper describes an end-to-end control system for autonomous navigation of a small vehicle at a remote place, e.g. in space for planetary exploration. Due to a realistic background of this study the proposed method has to deal with limited knowledge about the environment as well as limited system resources and operational boundary conditions, especially a very large time delay in the communication between the ground control station and the space segment. To overcome these constraints the remote system has to act in a very autonomous way. Ground support minimizes the computational load of the remote system. High-level information interchange reduces the communication bandwidth requirements.     

Application of solar and wave energies for long-range autonomous underwater vehicles

The solar-powered autonomous underwater vehicle (AUV) may have unlimited autonomous capability in time and be an efficient tool to explore the ocean. The performances of solar powered AUV, evidently, depend on available solar energy. The low efficiency of industrially produced solar panels (10-16%) affords sufficient amounts of energy at low latitudes, but does not at high latitudes of about 60° and more. On the contrary, available wave energy distribution increases with latitude. A similar relation of solar and wave energies occurs regarding their seasonal variations. Hence, the combination of solar and wave energies promises more efficient use of the vehicle at all latitudes over the whole year. Converters of wave energy to electrical energy are usually cumbersome mechanical structures unsuitable for installation on an AUV.In this sense, it is more reasonable to use wave energy to aid the vehicle's motion. In this case a very fortunate situation occurs. It was shown that the best shape for a solar vehicle is a wing. At the same time it is possible to transform wave oscillations to forward movement using three wings, fixed on the hull of the vehicle. In this way, the demands of efficient solar-powered and wave-driven vehicles fully coincide. These relationships are considered in the paper and some resulting data are given.     

Investigations on the Hybrid Tracking Control of an Underactuated Autonomous Underwater Robot

The problem of trajectory tracking control of an underactuated autonomous underwater robot (AUR) in a three-dimensional (3-D) space is investigated in this paper. The control of an underactuated robot is different from fully actuated robots in many aspects. In particular, these robot systems do not satisfy Brockett's necessary condition for feedback stabilization and no continuous time-invariant state feedback control law exists that makes a specified equilibrium of the closed-loop system asymptotically stable. The uncertainty of hydrodynamic parameters, along with the coupled, nonlinear dynamics of the underwater robot, also makes the navigation and tracking control a difficult task. The proposed hybrid control law is developed by combining sliding mode control (SMC) and classical proportional–integral–derivative (PID) control methods to reduce the tracking errors arising out of disturbances, as well as variations in vehicle parameters like buoyancy. Here, a trajectory planner computes the body-fixed linear and angular velocities, as well as vehicle orientations corresponding to a given 3-D inertial trajectory, which yields a feasible 6-d.o.f. trajectory. This trajectory is used to compute the control signals for the three available controllable inputs by the hybrid controller. A supervisory controller is used to switch between the SMC and PID control as per a predefined switching law. The switching function parameters are optimized using Taguchi design techniques. The effectiveness and performance of the proposed controller is investigated by comparing numerically with classical SMC and traditional linear control systems in the presence of disturbances. Numerical simulations using the full set of nonlinear equations of motion show that the controller does quite well in dealing with the plant nonlinearity and parameter uncertainties for trajectory tracking. The proposed controller response shows less tracking error without the usually present control chattering. Some practical features of this control law are also discussed.     

Terrain-Based Navigation for Underwater Vehicles Using an Ultrasonic Scanning System

In this paper an approach to the field of outdoor robotic navigation with a focus on underwater simultaneous localization and mapping (SLAM) is proposed that utilizes ultrasonic scanning images. Experimental results from the implementation of a SLAM algorithm with real data are presented. The projected landmark detection process constructs a map of the environment and generates navigation estimates based on an adaptive delayed nearest-neighbor algorithm. The feature extraction and validation processes are resolved at the sensor level using a simple local maximum-level detection algorithm on the range data. This paper presents experimental results from our research efforts in the above area, using data from water tank trials and a remotely operated vehicle operating in a shallow water environment.     

A practical and useful autonomous towed vehicle for port area inspection

This paper presents a novel underwater vehicle for port area inspection, which has various navigation modes (towed mode, autonomous mode and kite mode) to stand against fast and changeable sea currents. The property assures safe and reliable observation performance irrespective of current speed. Since in a port area sea currents are fast and complex, such a vehicle must be practical and useful for port area application. The unique point of the vehicle is the employment of an autonomous underwater vehicle (AUV) as a towed vehicle. In general, AUVs and towed vehicles are mutually contradictory. This paper describes the process of development to achieve the three different navigation modes. The system components and the results of computer simulations and towing tank tests to investigate the stability of the vehicle are presented. In addition, results of the first sea trial are also presented. These results show that the vehicle can navigate stably in the three different navigation modes.     

Development of autonomous underwater vehicles in Japan

In the hope of expanding underwater observation and research, the Institute of Industrial Science (IIS) at the University of Tokyo started extensive R&D on autonomous underwater vehicle (AUV) in 1984. IIS has constructed nine vehicles, including three ocean-going vehicles, one lake survey vehicle and various testbed vehicles. The R-One Robot is equipped with a closed-cycle diesel engine system and it successfully completed a 12-h operation of long-range autonomous diving in the Pacific Ocean in 1998. Utilizing the testbed robots, many intelligent systems, especially those for underwater vision systems, have been developed. The success of these AUVs at the IIS has led to the establishment of the 'Underwater Technology Research Center' which opened on 1 April 1999. This new center also plans to collaborate both nationally and internationally with other facilities for further R&D of AUVs and other new underwater observation technologies.     

An experimental investigation into the fault-tolerant control of an autonomous underwater vehicle

Autonomous underwater vehicles (AUVs) are expected to function in an unstructured underwater environment. One of the main requirements for effective operation in such an environment is to accommodate faults. In this paper, we have investigated a new approach to the allocation of thruster forces of an autonomous underwater vehicle under thruster faults. Generally, an AUV is equipped with more thrusters than what is minimally required to produce the desired motion. The proposed framework exploits the excess number of thrusters to accommodate thruster faults during operation. First, a redundancy resolution scheme is presented that considers the presence of excess number of thrusters along with any thruster faults and determines the reference thruster forces to produce the desired motion. These reference thruster forces are then utilized in the thruster controller to generate the required motion. This approach resolves the thruster redundancy in the Cartesian space and allows the AUV to track the task-space trajectories with asymptotic reduction of the task-space errors. Results from actual underwater experiments are provided to demonstrate the viability of the proposed scheme.     

Experimental study on fine motion control of underwater robots

This paper considers thruster dead zones and saturation limits, which are nonlinear elements that complicate fine motion control of underwater robots. If the vehicle is configured with redundant thrusters, the respective dead zones and their surrounding nonlinear regions could be avoided by implementing a null motion solution for the command input of the vehicle. This solution is derived from the vehicle's geometry and is realized before the application of the motion control algorithm. The result is an improvement in system performance exclusive of the implemented controller type. The approach is illustrated through simulation and experiment with an underwater robot, ODIN.     

Coordination of Multiple Control Schemes for Mobile Robot Navigation on the Basis of the Generalized Stochastic Petri-Nets

There have been two major streams of research for the motion control of mobile robots: model-based deliberate control and sensor-based reactive control. Since the two schemes have complementary advantages and disadvantages, each cannot completely replace the other. There are a variety of environmental conditions that affect the performance of navigation. The motivation of this study is that multiple motion control schemes are required to survive in dynamic real environments. In this paper, we exploit two discrete motion controllers for mobile robots. One is the deliberate trajectory tracking controller and the other is the reactive dynamic window approach. We propose the selective coordination of two controllers on the basis of the generalized stochastic Petri net (GSPN) framework. The major scope of this paper is to clarify the advantage of the proposed controller based on the coordination of multiple controllers from the results of quantitative performance comparison among motion controllers. For quantitative comparison, both simulations and experiments in dynamic environments were carried out. In addition, it is shown that navigation experiences are accumulated in the GSPN formalism. The performance of navigation service can be significantly improved owing to the automatically stored experiences.     

Optimal Guidance for Autonomous Underwater Vehicle Navigation within Undersea Areas of Current Disturbances

Simulated navigations of an autonomous underwater vehicle (AUV) achieved by the minimum time guidance within undersea areas of current disturbances are presented. When an AUV has to transit to a given destination within an area of current disturbance, ingenious guidance enables the minimum time navigation. In this study, a numerical solution procedure for an optimal heading guidance law is developed. As the optimal heading reference, the solution of the optimal guidance law is fed to the heading controller. Simulated optimal navigations are realized on the basis of the dynamics of an AUV 'r2D4'. The r2D4 is a deep-ocean-exploring AUV, developed by the Institute of Industrial Science, University of Tokyo. The developed procedure never fails to derive the optimal heading sequence within a finite computational time, provided that the current velocity in the navigation region is known a priori. As a fail-safe strategy in achieving the optimal navigation, the concept of quasi-optimal navigation is presented. The quasi-optimal navigation is implemented by on-site updates of optimal guidances followed by the heading tracking control.     

Hybrid autonomous control for multi mobile robots

Reinforcement learning can be an adaptive and flexible control method for autonomous system. It does not need a priori knowledge; behaviors to accomplish given tasks are obtained automatically by repeating trial and error. However, with increasing complexity of the system, the learning costs are increased exponentially. Thus, application to complex systems, like a many redundant d.o.f. robot and multi-agent system, is very difficult. In the previous works in this field, applications were restricted to simple robots and small multi-agent systems, and because of restricted functions of the simple systems that have less redundancy, effectiveness of reinforcement learning is restricted. In our previous works, we had taken these problems into consideration and had proposed new reinforcement learning algorithm, 'Q-learning with dynamic structuring of exploration space based on GA (QDSEGA)'. Effectiveness of QDSEGA for redundant robots has been demonstrated using a 12-legged robot and a 50-link manipulator. However, previous works on QDSEGA were restricted to redundant robots and it was impossible to apply it to multi mobile robots. In this paper, we extend our previous work on QDSEGA by combining a rule-based distributed control and propose a hybrid autonomous control method for multi mobile robots. To demonstrate the effectiveness of the proposed method, simulations of a transportation task by 10 mobile robots are carried out. As a result, effective behaviors have been obtained.     

An inertial navigation system for small autonomous underwater vehicles

A Small AUV Navigation System (SANS) is being developed at the Naval Postgraduate School. The SANS is an integrated GPS/inertial navigation system composed of low-cost, small-size components. It is designed to demonstrate the feasibility of using a low-cost inertial measurement unit to navigate between intermittent GPS fixes. This paper reports recent improvements to the SANS hardware, latest testing results and development of an asynchronous Kalman filter for improved position estimation.     

An Anthropomorphic Robotic Platform for Progressive and Adaptive Sensorimotor Learning

In recent years, advances and improvements in engineering and robotics have in part been due to strengthened interactions with the biological sciences. Robots that mimic the complexity and adaptability of biological systems have become a central goal in research and development in robotics. Usually, such a collaboration is addressed to a 2-fold perspective of (i) setting up anthropomorphic platforms as test beds for studies in neuroscience and (ii) promoting new mechatronic and robotic technologies for the development of bio-inspired or humanoid high-performance robotic platforms. This paper provides a brief overview of recent studies on sensorimotor coordination in human motor control and proposes a novel paradigm of adaptive learning for sensorimotor control, based on a multi-network high-level control architecture. The proposed neurobiologically inspired model has been applied to a robotic platform, purposely designed to provide anthropomorphic solutions to neuroscientific requirements. The goal of this work is to use the bio-inspired robotic platform as a test bed for validating the proposed model of high-level sensorimotor control, with the aim of demonstrating adaptive and modular control based on acquired competences, with a higher degree of flexibility and generality than conventional robotic controllers, while preserving their robustness. To this purpose, a set of object-dependent, visually guided reach-and-grasp tasks and the associated training phases were first implemented in a multi-network control architecture in simulation. Subsequently, the offline learning realized in simulation was used to produce the input command of reach-and-grasp to the low-level position control of the robotic platform. Experimental trials demonstrated that the adaptive and modular high-level control allowed reaching and grasping of objects located at different positions and objects of variable size, shape and orientation. A future goal would be to address autonomous and progressive learning based on growing competences.     

Differential GPS and odometry-based outdoor navigation of a mobile robot

This paper describes outdoor navigation for a mobile robot by using differential GPS (DGPS) and odometry in a campus walkway environment. The robot position is estimated by fusion of DGPS and odometry. The GPS receiver measures its position by radio waves from GPS satellites. The error of GPS measurement data increases near high buildings and trees because of multi-path and forward diffractions. Thus, it is necessary to pick up only accurate DGPS measurement data when the robot position is modified by fusing DGPS and odometry. In this paper, typical DGPS measurement data observed near high buildings and trees are reported. Then, the authors propose a novel position correction method by fusing GPS and odometry. Fusion of DGPS and odometry is realized using an extended Kalman filter framework. Moreover, outdoor navigation for a mobile robot is accomplished by using the proposed correction method.     

Reinforcement learning-based group navigation approach for multiple autonomous robotic systems

In several complex applications, the use of multiple autonomous robotic systems (ARS) becomes necessary to achieve different tasks, such as foraging and transport of heavy and large objects, with less cost and more efficiency. They have to achieve a high level of flexibility, adaptability and efficiency in real environments. In this paper, a reinforcement learning (RL)-based group navigation approach for multiple ARS is suggested. Indeed, the robots must have the ability to form geometric figures and navigate without collisions while maintaining the formation. Thus, each robot must learn how to take its place in the formation, and avoid obstacles and other ARS from its interaction with the environment. This approach must provide ARS with the capability to acquire the group navigation approach among several ARS from elementary behaviors by learning with trialand-error search. Then, simulation results display the ability of the suggested approach to provide ARS with capability to navigate in a group formation in dynamic environments. With its cooperative behavior, this approach makes ARS able to work together to successfully fulfill the desired task.     

Heavy material handling by cooperative robot control

Multifingered dextrous robot hands can perform more complex tasks than simpler end effectors. Teleoperation, in which a robot mimics the motion of a remote operator, provides a convenient method for controlling these robot hands. Damage to the object being manipulated by the robot hand may result in the case of open-loop control if there is no force-feedback sensation to the operator from the robot hand. The need arises for new actuator technology to provide force feedback to the hand master. These actuators have to meet the tight space and light weight requirements of a dextrous master. One candidate is the shape memory alloy (SMA) actuator. SMAs, such as Nitinol, are materials with a unique 'mechanical memory' and high force/weight ratio. A prototype SMA actuator and its hardware interface were designed and tested. Results showed that the actuator met the space and weight limitations of the master (Exos DHM?) and provided adequate reactive force feedback to the operator. However, the actuator had a low bandwidth of operation, due to relatively slow engagement and disengagement motions. This makes it unusable in real-time control situations.     

Realization of a Pheromone Potential Field for Autonomous Navigation by Radio Frequency Identification

This paper presents the results of our research that aims to implement autonomous navigation with an artificial pheromone system. As social insects, a group of ants show advanced performance in their activity by using a chemical substance called a pheromone. By introducing an artificial pheromone system composed of data carriers and autonomous robots, the robotic system creates a potential field to navigate their group. Using this approach we have developed a pheromone density model to realize the function of pheromones with the help of data carriers. We intend to show the effectiveness of the proposed system by performing computer simulations and real experiments for one and two dimensions. The proposed system can be used for an autonomous navigation system. Results are discussed and future works are proposed.