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.     

Decentralized Traffic Control for Non-Holonomic Flexible Automated Guided Vehicles in Industrial Environments

This paper deals with the problem of coordinating flexible automated guided vehicles (AGVs) in real manufacturing systems. The problem consists of ensuring safe and successful task execution while several AGVs operate as a distributed transportation system in real industrial environments. The proposed solution combines different decentralized techniques to increase the flexibility and scalability of the multirobot system. The coordination is addressed by dividing the problem into path planning, obstacle avoidance and traffic control problems. The path planning method takes into account the location of mates for replanning the routes. The obstacle avoidance technique considers the kinematic constraints of the platform for reactive motion control. The traffic control approach makes use of a decentralized control policy that takes into account the capabilities of vehicles. By combining all these techniques and configuring the system properly, we present the successful development of a distributed transportation system composed of a team of flexible AGVs. The proposed solution has been validated using both a set of custom-modified AGVs operating in a real factory and a simulation of several AGVs operating in a virtual scenario.     

A roadmap construction algorithm for mobile robot path planning using skeleton maps

Path planning using conventional roadmaps, such as visibility graphs, probability roadmaps and skeleton maps, may have some disadvantages of long length, sharp turns or collisions with obstacles. Specifically, the paths using the conventional skeleton map have unnecessary turns around crossing points, which make longer paths and prevent the robot from moving smoothly. To improve the skeleton map, this paper proposes a new roadmap construction algorithm for path planning of a mobile robot using skeleton maps. The proposed algorithm alleviates the problems of the conventional algorithms by constructing roadmaps which consist of polygons around the crossing points. Simulation results show the efficiency of the proposed algorithm by comparing the results with those obtained using the conventional algorithm.     

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.     

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.     

A tree architecture with hierarchical data processing on a sensor-rich hexapod robot

This paper presents the hardware and software architecture of Golem, a hexapod robot designed as a flexible, scalable, general purpose development and experimenting tool targeted to academia, industry, and defense environments. The system is technologically innovative in its architecture, performance, size and integration, and is industrially promising in its filling the gap between low-performance commercial solutions and costly application-specific proprietary solutions.     

Application of Genetic Algorithms for biped robot gait synthesis optimization during walking and going up-stairs

Selecting an appropriate gait can reduce consumed energy by a biped robot. In this paper, a Genetic Algorithm gait synthesis method is proposed, which generates the angle trajectories based on the minimum consumed energy and minimum torque change. The gait synthesis is considered for two cases: walking and going up-stairs. The proposed method can be applied for a wide range of step lengths and step times during walking; or step lengths, stair heights and step times for going up-stairs. The angle trajectories are generated without neglecting the stability of the biped robot. The angle trajectories can be generated for other tasks to be performed by the biped robot, like going down-stairs, overcoming obstacles, etc. In order to verify the effectiveness of the proposed method, the results for minimum consumed energy and minimum torque change are compared. A Radial Basis Function Neural Network is considered for the real-time application. Simulations are realized based upon the parameters of the 'Bonten-Maru I'humanoid robot, which is under development in our laboratory. The evaluation by simulations shows that the proposed method has a good performance.     

High-speed positioning of an industrial robot based on Preview-Learning control

In this study, a numerical procedure for designing kinematic parameters of SCARA-type manipulators is proposed to yield such a design that the resulting manipulator has the fastest cycle time for a given task. To achieve this goal, an optimization problem is formulated to minimize the cycle time by determining geometric parameters such as the link lengths and the locations of manipulators as well as the trajectory. The representative task to get the cycle time is defined as CP (continuous path) motion along the path crisscrossing the standard working area. A gradient projection algorithm is used to obtain the optimal design with the assumption that each actuator should exert a torque and angular velocity within the capacity of specific commercially available direct-drive motors. SCARA-type manipulators of both absolute coordinate and relative coordinate types are designed to reduce the cycle times. The results show that the absolute coordinate manipulator produces a shorter cycle time than the relative coordinate manipulator in optimal designs.     

A globally stable state feedback controller for flexible joint robots

The paper addresses the problem of controlling the joints of a flexible joint robot with a state feedback controller and proposes a gradual way of extending such a controller towards the complete decoupling of the robot dynamics. The global asymptotic stability for the state feedback controller with gravity compensation is proven, followed by some theoretical remarks on its passivity properties. By proper parameterization, the proposed controller structure can implement a position, a stiffness or a torque controller. Experimental results on the DLR lightweight robots validate the method.     

A fast,accurate and robust method for self-localization in polygonal environments using laser range finders

Self-localization is important in almost all robotic tasks. For playing an aesthetic and effective game of robotic soccer, self-localization is a necessary prerequisite. When we designed our robotic soccer team for participating in robotic soccer competitions, it turned out that none of the existing approaches met our requirements of being fast, accurate and robust. For this reason, we developed a new method, which is presented and analyzed in this paper. This method is one of the key components and is probably one of the explanations for the success of our team in national and international competitions. We also present experimental evidence that our method outperforms other self-localization methods in the RoboCup environment.     

Mechanical planning and actual test results of a robot for painting the exterior walls of high-rise buildings

A robot developed for repainting the exterior walls of Tokyo's Shinjuku Center Building (54 stories above and 3 stories below the ground, and 219.5 m high) is introduced with an explanation of its mechanism and a demonstration of its actual use. The first robot of its kind developed in Japan successfully demonstrated its capability to complete its mission of painting an area of 95,400 m² while automatically avoiding glass and openings.     

CRABOT: A Biomimetic Burrowing Robot Designed for Underground Chemical Source Location

This paper describes the biomimetic inspiration and development of a burrowing robot called CRABOT. This robot is one part of a project to investigate novel techniques for locating the source of volatile chemicals released underground. A range of chemicals, including petrol, kerosene and diesel fuel, are commonly stored in underground tanks or transported by buried pipelines. All of these structures are prone to corrosion and the development of leaks. Currently, finding the source of underground chemical leaks is a difficult task. As part of an automated system to locate chemical leaks a prototype burrowing robot has been developed modeled on the mole crab Emerita talpoida. The current version of this robot functions in a 'semi-submersed' configuration that allows the operation of the burrowing mechanism to be easily observed. Later versions will burrow completely below the surface. This paper provides details of the design and performance of the prototype burrowing robot.     

Unified nonsingular tracking and stabilization controller design for unicycle-type wheeled mobile robots

A unified, singularity-avoidant controller which enables simultaneous trajectory tracking and posture stabilization of unicycle-type wheeled mobile robots is proposed. The design scheme is based on phase portrait analysis, dynamic feedback linearization and sliding mode control. Path planning via phase portrait analysis plays a key role in choosing the control parameters and the initial value of the extended state in avoiding any singularity. Simulation results on posture stabilization as well as an eight-shaped trajectory tracking are presented to demonstrate the performance of the proposed controller.     

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 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.     

On the Experiment Design for Direct Dynamic Parameter Identification of Parallel Robots

Accurate robot dynamic models require the estimation and validation of the dynamic parameters through experiments. To this end, when performing the experiments, the system has to be properly excited so that the unknown parameters can be accurately estimated. The experiment design basically consists of optimizing the trajectory executed by the robot during the experiment. Due to the restricted workspace with parallel robots this task is more challenging than for serial robots; thus, this paper is focused on the experiment design aimed at dynamic parameter identification of parallel robots. Moreover, a multicriteria algorithm is proposed in order to reduce the deficiencies derived from the single-criterion optimization. The results of the identification using trajectories based on a single criterion and the multicriteria approaches are compared, showing that the proposed optimization can be considered as a suitable procedure for designing exciting trajectories for parameter identification.     

Augmented reality for visualization the narrow areas in jaw surgery: modified Correntropy based enhanced ICP algorithm

Multimedia Tools and Applications - Over time, Augmented Reality (AR) based technology becomes not being properly to implement with oral and maxillofacial surgery to visualise the narrow area spot...     

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.