Visual feedback control of a robot in an unknown environment (learning control using neural networks)

In this paper, a visual feedback control approach based on neural networks is presented for a robot with a camera installed on its end-effector to trace an object in an unknown environment. First, the one-to-one mapping relations between the image feature domain of the object to the joint angle domain of the robot are derived. Second, a method is proposed to generate a desired trajectory of the robot by measuring the image feature parameters of the object. Third, a multilayer neural network is used for off-line learning of the mapping relations so as to produce on-line the reference inputs for the robot. Fourth, a learning controller based on a multilayer neural network is designed for realizing the visual feedback control of the robot. Last, the effectiveness of the present approach is verified by tracing a curved line using a 6-degrees-of-freedom robot with a CCD camera installed on its end-effector. The present approach does not necessitate the tedious calibration of the CCD camera and the complicated coordinate transformations.

A reinforcement learning approach for robot control in an unknown environment

In this paper, a control approach based on reinforcement learning is present for a robot to complete a dynamic task in an unknown environment. First, a temporal difference-based reinforcement learning algorithm and its evaluation function are used to make the robot learn with its trials and errors as well as experiences. Second, the simulation are carried out to adjust the parameters of the learning algorithm and determine an optimal policy by using the models of a robot. Last, the effectiveness of the present approach is demonstrated by balancing an inverse pendulum in the unknown environment.

Flowchart software for a modular robot

Flowcharting is a common method of setting out the requirements for a piece of code. It is simple with few rules to follow. Rarely however, is it used as the code itself. This paper describes the outline of a software package that uses the flowchart as the code for a small, autonomous, modular robot, designed for use in High Schools and Universities at an introductory level. By using flowcharting the student is introduced to the concept of structured programming. A flowchart is often the first step in programming. Here it is the only step, easing the student into the art of coding, and simplifying the teachers job.

Flowchart and kernel software for modular robot

Flowcharting is a common method of setting out the requirements for a piece of code. It is simple with few rules to follow. Rarely however, s it used as the code itself. This paper describes the outline of a software package that uses the flowchart as the code for a small, autonomous, modular robot, designed for use in High Schools. It also describe the code used by the robot to complement the flowchart software creating a system that can be used by students and their teachers to design, build and program a robot without previous programming experience.

An autonomous trimming system of large glass fiber reinforced plastics parts using an omni-directional mobile robot and its control

This paper describes an automated trimming system of large glass fiber reinforced plastic (GFRP) using an omni-directional wheeled mobile robot (WMR) and its path control method. In trimming GFRP parts, much glass fiber and plastic powder dust occur and it becomes bad visible in environment. It is necessary to correct dead-reckoning errors of the WMR in order to control its moving path. We have discussed an external correction method of the dead-reckoning errors for the WMR using ultrasonic sensor.

Path planning for sensor data collecting mobile robot

A mobile robot employed for data collection is faced with the problem of travelling from an initial location to a final location while maintaining as close a distance as possible to all the sensors at a given time in the journey. Here we employ optimal control ideas in forming the necessary control commands for such a robot resulting not only the necessary acceleration commands for the underlying robot, but also the resulting trajectory. This approach can also be easily extended for the case of producing the optimal trajectory for an ariel vehicle used for data collection from indiscriminately scattered ad-hoc sensors located on the ground. We demonstrate the implementation of our algorithm using a Pioneer 3-AT robot.

Bilateral haptic teleoperation of an articulated track mobile robot

Teleoperation has been used in many applications, allowing a human operator to remotely control a robotic system in order to perform a particular task. Recently haptic teleoperation has focused mainly on improving performance in remote manipulation tasks, however the haptic approach offers similar advantages for teleoperative control of the motion of a mobile robot. This paper describes a prototype system designed to facilitate haptic teleoperation of an all-terrain, articulated track mobile robot. This system utilizes a multi-modal user interface intended to improve operator immersion, reduce operator overload and improve teleoperative task performance. The system architecture facilitates implementation of an application-specific haptic augmentation algorithm in order to improve operator performance in challenging real-world tasks. The contributions of this work can be categorized as the custom mobile platform, teleoperator interface and haptic augmentation strategy.

Simulating autonomous robot teams with Microsoft robotics studio

This paper presents an application of Microsoft Robotics Studio (MSRS) in which a team of six four wheel drive, ground based robots explore and map simulated terrain. The user has the ability to modify the terrain and assign destination objectives to the team while the simulation is running. The terrain is initially generated using a gray scale image, in which the intensity of each pixel in the image gives an altitude datum. The robots start with no knowledge of their surroundings, and map the terrain as they attempt to reach user-defined target objectives. The mapping process simulates the use of common sensory hardware to determine datum points, including provision for field of view, detection range, and measurement accuracy. If traversal of a mapped area is indicated by the users’ targeting commands, path planning heuristics developed for MSRS by the author in earlier work are used to determine an efficient series of waypoints to reach the objective. Mutability of terrain is also explored- the user is able to modify the terrain without stopping the simulation. This forces the robots to adapt to changing environmental conditions, and permits analysis of the robustness of mapping algorithms used when faced with a changing world.

Heavy tools manipulation by low powered direct-drive five-bar parallel robot

This paper presents a simple and available system for manipulation of heavy tools by low powered manipulator for industrial applications. In the heavy manufacturing industries, sometimes, heavy tools are employed for different types of work. But the application of robots with heavy tools is not possible due to the limited torque limits of actuators. Suspended tool systems (STS) have been proposed to manipulate heavy tools by low powered robot-arm for this purpose. A low powered five-bar direct-drive parallel manipulator is designed and constructed to manipulate heavy tools suspended from a spring balancer. The validity, usefulness, and effectiveness of the suspended tool system are shown by experimental results.

Multi-robot hunting in dynamic environments

This paper is concerned with multi-robot hunting in dynamic environments. A BCSLA approach is proposed to allow mobile robots to capture an intelligent evader. During the process of hunting, four states including dispersion-random-search, surrounding, catch and prediction are employed. In order to ensure each robot appropriate movement in each state, a series of strategies are developed in this paper. The dispersion-search strategy enables the robots to find the evader effectively. The leader-adjusting strategy aims to improve the hunting robots’ response to environmental changes and the outflank strategy is proposed for the hunting robots to force the evader to enter a besieging circle. The catch strategy is designed for shrinking the besieging circle to catch the evader. The predict strategy allows the robots to predict the evader’s position when they lose the tracking information about the evader. A novel collision-free motion strategy is also presented in this paper, which is called the direction-optimization strategy. To test the effect of cooperative hunting, the target to be captured owns a safety-motion strategy, which helps it to escape being captured. The computer simulations support the rationality of the approach.

A 3-D locomotion biomimetic robot fish with information relay

In this paper, a biomimetic robot fish is designed. It has a biomimetic tail to simulate the carangiform tail, a barycenter-adjustor for descending/ascending motions, multiple sensors, and it may communicate with the outside by an information relay system on water. Combining the movements of the tail and the structure for descending and ascending, the robot fish can simulate the swimming of real fish in water and a biomimetic motion library is established. Finally, the prototype and experiments are given.

Simulation of underwater robots using MS Robot Studio©

One stage in designing the control for underwater robot swarms is to confirm the control algorithms via simulation. To perform the simulation Microsoftpsilas Robotic Studiocopy was chosen. The problem with this simulator and others like it is that it is set up for land-based robots only. This paper explores one possible way to get around this limitation. This solution cannot only work for underwater vehicles but aerial vehicles as well.

Design and analysis of hull configurations for a low-cost, autonomous underwater robot as an enabling technology for system of system applications

The objective of this research is to model and analyze candidate hull configurations for a low-cost, modular, autonomous underwater robot. As the computational power and speed of microprocessors continue to progress, we are seeing a growth in the research, development, and the utilization of underwater robots. The number of applications is broadening in the R&D and science communities, especially in the area of multiple, collaborative robots. These underwater collaborative robots represent an instantiation of a System of Systems (SoS). While each new researcher explores a unique application, control method, etc. a new underwater robot vehicle is designed, developed, and deployed. This sometimes leads to one-off designs that are costly. One limit to the wide-scale utilization of underwater robotics is the cost of development. Another limit is the ability to modify the configuration for new applications and evolving requirements. Consequently, we are exploring autonomous underwater vehicle (AUV) hull designs towards the goal of modularity, vehicle dexterity, and minimizing the cost. In our analysis, we have employed 3D solid modeling tools and finite element methods. In this paper we present our initial results and discuss ongoing work.