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.

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.

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.

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.

Terminal approach navigation for autonomous robots in a sensory network

In this paper we present a technique based on precision guidance approach for the sensor delivery and reception problem between two mobile robots. A slave robot is employed to collect sensors and slack them on a tray carried by the mobile master robot. We define the terminal attitude of the slave robot with respect to the master and present a LQR control approach to solving the problem of achieving a desired terminal approach angle necessary for the appropriate sensor delivery. The approach criteria is defined in terms of both minimizing the miss distance and controlling the slave robot's body attitude with respect to the master robot at the terminal point.

Using autonomous mobile agents for efficient data collection in sensor networks

Sensor networks are emerging as the new frontier in sensing technology, however there are still issues that need to be addressed. Two such issues are data collection and energy conservation. We consider a mobile robot, or a mobile agent, traveling the network collecting information from the sensors themselves before their onboard memory storage buffers are full. A novel algorithm is presented that is an adaptation of a local search algorithm for a special case of the Asymmetric Traveling Salesman Problem with Time-windows (ATSPTW) for solving the dynamic scheduling problem of what nodes are to be visited so that the information collected is not lost. Our algorithms are given and compared to other work.

Optimization-based formation of autonomous mobile robots

The formation of autonomous mobile robots to an arbitrary geometric pattern in a distributed fashion is a fundamental problem in formation control. This paper presents a new asynchronous, memoryless (oblivious) algorithm to the formation problem via distributed optimization techniques. The optimization minimizes an appropriately defined difference function between the current robot distribution and the target geometric pattern. The optimization processes are performed independently by individual robots in their local coordinate systems. A movement strategy derived from the results of the distributed optimizations guarantees that every movement makes the current robot configuration approaches the target geometric pattern until the final pattern is reached.

Towards autonomous image fusion

Mobile robots are providing great assistance operating in hazardous environments such as nuclear cores, battlefields, natural disasters, and even at the nano-level of human cells. These robots are usually equipped with a wide variety of sensors in order to collect data and guide their navigation. Whether a single robot operating all sensors or a swarm of cooperating robots operating their special sensors, the captured data can be too large to be transferred across limited resources (e.g. bandwidth, battery, processing, and response time) in hazardous environments. Therefore, local computations have to be carried out on board the swarming robots to assess the worthiness of captured data and the capacity of fused information in a certain spatial dimension as well as selection of proper combination of fusion algorithms and metrics. This paper introduces to the concepts of Type-I and Type-II fusion errors, fusion capacity, and fusion worthiness. These concepts together form the ladder leading to autonomous fusion systems.

Formation control of weak autonomous robots

Formation of autonomous mobile robots to an arbitrary geometric pattern in a distributed fashion is a fundamental problem in formation control. This paper presents a new fully distributed, memoryless (oblivious) algorithm to the formation control problem via distributed optimization techniques. The optimization minimizes an appropriately defined difference function between the current robot distribution and target geometric pattern. The optimization processes are performed independently by individual robots in their local coordinate system. A movement strategy derived from the results of the distributed optimizations guarantees that every movement makes the current robot configuration approaches the target geometric pattern until the final pattern is reached.

Insect based navigation and its applications to the autonomous control of mobile robots

Giving robots the ability to autonomously move around in various real-world environments has been a major goal of AI (artificial intelligence) for quite some time. To this end it is vital for robots to be able to perceive their surroundings in 3D; they must be able to estimate the range of obstacles in their path.

Animals navigate through various uncontrolled environments with seemingly little effort. Flying insects, especially, are quite adept at manoeuvring in complex, unpredictable and possibly hostile and hazardous environments.

In this paper it is shown that very simple motion cues, inspired by the visual navigation of flying insects, can be used to provide a mobile robot with the ability to successfully traverse a corridor environment. Equipping an autonomous mobile robot with the ability to successfully navigate real-word environments (in real-time) constitutes a major challenge for AI and robotics. It is in this area that insect based navigation has something to offer.

Insect inspired behaviours for the autonomous control of mobile robots

Animals navigate through various uncontrolled environments with seemingly little effort. Flying insects, especially, are quite adept at manoeuvring in complex, unpredictable and possibly hostile environments. Through both simulation and real-world experiments, we demonstrate the feasibility of equipping a mobile robot with the ability to navigate a corridor environment, in real time, using principles based on insect-based visual guidance. In particular we have used the bees’ navigational strategy of measuring object range in terms of image velocity. We have also shown the viability and usefulness of various other insect behaviours: (i) keeping walls equidistant, (ii) slowing down when approaching an object, (iii) regulating speed according to tunnel width, and (iv) using visual motion as a measure of distance travelled.

Spiking neural network-based target tracking control for autonomous mobile robots

In this paper, a target tracking controller based on spiking neural network is proposed for autonomous robots. This controller encodes the preprocessed environmental and target information provided by CCD cameras, encoders and ultrasonic sensors into spike trains, which are integrated by a three-layer spiking neural network (SNN). The outputs of SNN are generated based on the competition between the forward/backward neuron pair corresponding to each motor, with the weights evolved by the Hebbian learning. The application to target tracking of a mobile robot in unknown environment verifies the validity of the proposed controller.

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.