Robot Route Research Articles

A Visual Navigation Method of Mobile Robot Using a Sketched Semantic Map

A new visual navigation method for a mobile robot is proposed in this paper. Its originality lies in integrating a sketched map with a semantic map together for the robot's navigation and in using unified tags to help recognize landmarks. In this sketched semantic map, the outline and semantic information of key referenced objects are used to represent themselves and a rough route for the robot's navigation is also sketched. Over the course of robot navigation along the route, and in order to easily recognize the referenced objects from the complex background, a kind of unified label is designed and pasted on the potential referenced objects in advance. A recognition method based on the Pseudo-Zernike Moment and the Normalized Moment of Inertia is used to compute the matching degree between the real-time image of the referenced object and its similar outline in a database. In addition, the odometer information is also fused so as to roughly localize the robot. Finally, through a series of experiments, the advantage and efficiency of the new navigation method with real-time dynamic obstacle avoidance are testified with the help of the imprecise real map and route.

Implementation of robot routing approaches for convoy merging manoeuvres

Autonomous and cooperative guidance strategies for a convoy of electric vehicles in an urban context are challenging research topics in robotics and intelligent transportation systems. The vehicles that form the convoy eventually will have to leave it to perform a mission and return to the convoy formation once the mission has been accomplished. Nevertheless, the merging manoeuvres amongst the convoy and the units returning to it (pursuing units) is a complex task that involves the determination of the best merging point and the route across the city to reach it. This paper tackles this routing problem of a robot located in a map that is trying to join a convoy of robots in constant movement along a peripheral trajectory. We have developed two search strategies able to determine the optimal merging point and the best route to reach it: on one hand we describe a basic solution able to solve the problem when the time spent by the robot traveling along every street of the map is considered to be known and constant. On the other hand, we extended this basic approach to provide a new search strategy that considers uncertainty in traveling times. This increases considerably the complexity of the problem and makes necessary the inclusion of a risk factor that must be considered when determining the best route and the merging point for the manoeuvre. We also put our search strategies into practice in both, simulated and real scenarios. On one hand we have simulated the behavior of a convoy leader and a transport unit which is trying to join in the convoy, using Player&Stage. On the other hand we have used real P3-DX robot units as prototypes of electrical vehicles in a transport scenario.

Visually-extended vector polar histogram applied to robot route navigation

This paper presents a visual extension of the vector polar histogram (VVPH) for safe and fast real-time obstacle avoidance and navigation in route environments. VVPH is based on an enhanced vector polar histogram method (VPH+). VPH+ is a powerfully performing method in obstacle avoidance and navigation. It depends on highly accurate sensors, such as a laser range finder. The accuracy of visual data for route environments is enhanced using the hidden Markov model (HMM) and extended Kalman filter (EKF). HMM yields faster estimation results in route environments, preventing the smoothing effect of the EKF causing unexpected errors in a situation where features disappear suddenly. The performance of the proposed method, VVPH, is verified via computer simulations and experimental setups, in terms of the total travelling time and the accuracy of the visual histogram.

A spatial orthogonal allocation and heterogeneous cultural hybrid algorithm for multirobot exploration mission planning

A spatial orthogonal allocation method is devised for multirobot tasks allocation. A 3D space model is adopted to describe exploration mission; meanwhile spatial orthogonal tentative technology is utilized to update the attractor position for load balance. Heterogeneous interactive cultural hybrid architecture is proposed to solve a robot route planning problem; it utilizes good-point-set to initialize population spaces, redefine novel evolution model and particle evolution ability, and introduce near-neighbor local search strategy in order to enhance search capability. Finally, spatial orthogonal allocation and heterogeneous cultural hybrid algorithm (SOAHCHA) are verified by simulation analysis and MORCS2 planning experiments; those results show that the proposed algorithm is efficient because of its successful performance and balanced allocation.

Surveying Robot Routing Algorithms With Data Mining Approach

Data mining knowledge in response to technological advances in various Rmynh, foot arena is built there. Data Mining face a different situation that the data size is large and we want to build a small model and not too complicated and yet the data as well as describe. Necessity to use data analysis to reduce the amount and the huge volume of information. One important and practical issues in the world of machine intelligence and is robotics robots routing. Robot router has obstacle detection and how to deal with the decision with obstacle. For routing, algorithms including probabilistic methods (filtering particulate), evolutionary algorithms such as genetic, ants social and optimization particle mass, neural methods - Fuzzy, inequality of matrix method based on gradient methods combined sensor information, etc. There are data mining methods in the years 2010-2008 as a technique for routing and a complete robot has been used and still is in progress. Overview of the methods in the paper mentioned in various articles since 2000 has so far. Although many data mining methods include, but mentioned in this article with specific literature data mining will deal with the routing problem.

A faster algorithm for 2-cyclic robotic scheduling with a fixed robot route and interval processing times

Consider an m-machine production line for processing identical parts served by a mobile robot. The problem is to find the minimum cycle time for 2-cyclic schedules, in which exactly two parts enter and two parts leave the production line during each cycle. This work treats a special case of the 2-cyclic robot scheduling problem when the robot route is given and the operation durations are to be chosen from prescribed intervals. The problem was previously proved to be polynomially solvable in O( m 8log m) time. This paper proposes an improved algorithm with reduced complexity O( m 4).

Robot Path Routing for Shortest Moving Distance in Wireless Robotic Sensor Networks

The wireless robotic sensor network (WRSN) is a combination of a mobile robot and wireless sensor networks. In WRSN, robots perform high-level missions such as human rescue, exploration in dangerous areas, and maintenance and repair of unmanned networks in cooperation with surrounding sensor nodes. In such a network, robots should move to the accident site as soon as possible. This paper proposes a distance-aware robot routing (DAR) algorithm, which focuses on how to pick the shortest path for the mobile robot by considering characteristics different from packet routing. Simulations are performed to demonstrate the benefits of using the proposed algorithm.

Parametric algorithms for 2-cyclic robot scheduling with interval processing times

Consider an m-machine production line for processing identical parts served by a mobile robot. The problem is to find the minimum cycle time for 2-cyclic schedules, that is, schedules in which exactly two parts enter and two parts leave the production line during each cycle. This work treats a special case of the 2-cyclic robot scheduling problem when the robot route is given and operation durations are chosen from prescribed intervals. A strongly polynomial algorithm of time complexity O(m 8log?m) is proposed.

Robot route stacks-up neatly for Marley

Robot route stacks-up neatly for Marley

New robotic routing system from KMT Robotic Solutions specially designed for trimming acrylic bath tubs

New robotic routing system from KMT Robotic Solutions specially designed for trimming acrylic bath tubs

A Parametric Algorithm for 2-Cyclic Robotic Scheduling with Interval Processing Times

Consider an m -machine production line for processing identical parts served by a mobile robot. The problem is to find the minimum cycle time for 2-cyclic schedules, in which exactly two parts enter and two parts leave the production line during each production cycle. This paper treats a case of 2-cyclic robot scheduling in which the robot route is given and the operation durations are to be chosen from prescribed intervals. A strongly polynomial algorithm of complexity O ( m 4 ) is proposed.

Robot Topological Map Generation from Formal Route Instructions

Mobile robots and Humanoids need to use spatial information about their surrounding environment in order to effectively plan and execute navigation tasks. This spatial information can be presented in various ways to increase the interaction between the human and the robot. One of the more effective ways is by describing the route verbally which bridges the gap between the forms of spatial knowledge of such robots and the forms of language used by humans.In this paper, we build a topological map for robot route description. This map represents the route’s motion actions and spatial relationships graphically to plan robot’s navigation task. The map is generated by using Formal Route Instructions (FRIs) to simplify the route description process and also to avoid ambiguity. FRIs are designed to be simple, easy to use, and suitable for naive users.

On the Optimal Robot Routing Problem in Wireless Sensor Networks

This paper targets the identification of outlying sensors (that is, outlying reading sensors) and the detection of the reach of events in sensor networks. Typical applications include the detection of the transportation front line of some vegetation or animalcule's growth over a certain geographical region. We propose and analyze two novel algorithms for outlying sensor identification and event boundary detection. These algorithms are purely localized and, thus, scale well to large sensor networks. Their computational overhead is low, since only simple numerical operations are involved. Simulation results indicate that these algorithms can clearly detect the event boundary and can identify outlying sensors with a high accuracy and a low false alarm rate when as many as 20 percent sensors report outlying readings. Our work is exploratory in that the proposed algorithms can accept any kind of scalar values as inputs?a dramatic improvement over existing work, which takes only 0/1 decision predicates. Therefore, our algorithms are generic. They can be applied as long as events? can be modeled by numerical numbers. Though designed for sensor networks, our algorithms can be applied to the outlier detection and regional data analysis in spatial data mining.

Symbolic Trajectory Description in Mobile Robotics

Autonomous mobile robot navigation systems are based on three principal kinds of techniques: map-based navigation, map-building-based navigation and mapless navigation. We propose a method for symbolic trajectory description in unknown indoor environments. The chosen form uses a panoramic description called fresco. The method uses distance measurements from a 2D laser range finder, digitises the robot's visibility area, eliminates superfluous data and reorients their presentation. The landmarks are then extracted and organised into the fresco which is validated by means of neighbourhood rules. As the robot moves in the environment, the frescoes are created and both the amount of new information a fresco carries out and its position in relation to the preceding ones are evaluated by means of two criteria. Only frescoes selected as enough informative are stored to describe the robot's route.

Symbolic environment representation by means of frescoes in mobile robotics

Autonomous mobile robot navigation systems are based on three principal kinds of techniques: map-based navigation, map-building-based navigation and mapless navigation. We propose a mapless method for trajectory description in unknown indoor environments. The method uses distance measurements from a 2D laser range finder, digitises the robot's visibility area, eliminates superfluous data and reorients their presentation with laws similar to those used in cellular automata. The landmarks are extracted and organised in a panoramic description called fresco. The frescoes which are validated by means of neighbourhood rules. The most informative frescoes are detected by means of two criteria and stored. The stored frescoes are considered as a human-like descritption of the robot's route and could be used by the robot to retrieve its route to its starting point.

An Effective Algorithm for the Futile Questioning Problem

In the futile questioning problem, one must decide whether acquisition of additional information can possibly lead to the proof of a conclusion. Solution of that problem demands evaluation of a quantified Boolean formula at the second level of the polynomial hierarchy. The same evaluation problem, called Q-ALL SAT, arises in many other applications. In this paper, we introduce a special subclass of Q-ALL SAT that is at the first level of the polynomial hierarchy. We develop a solution algorithm for the general case that uses a backtracking search and a new form of learning of clauses. Results are reported for two sets of instances involving a robot route problem and a game problem. For these instances, the algorithm is substantially faster than state-of-the-art solvers for quantified Boolean formulas.

Harley‐Davidson buff saddlebags

Product quality improved and finishing cost per saddlebag was reduced when robotic routing, drilling and sanding was instituted at Harley‐Davidson, an American motorcycle builder. Careful planning, and smart engineering all helped smooth the commissioning while not displacing workers.

"Ready" to go robot routing system minimises on site programming and commissioning costs

"Ready" to go robot routing system minimises on site programming and commissioning costs

Rough level path planning method for a robot using SOFM neural network

In this paper a path planning method for off-line programming of a joint robot is described. The method can automatically choose the easiest and safest route for an industrial robot from one position to another. The method is based on the use of a Self Organised Feature Map (SOFM) neural network. By using the SOFM neural network the method can adapt to different working environments of the robot. According to test results one can conclude that the SOFM neural network is a useful tool for the path planning problem of a robot.

Cyclic Scheduling of Operations for a Part Type in an FMS Handled by a Single Robot: A Parametric Critical-Path Approach

We consider two problems of periodic scheduling of parts in a robotic production system functioning under a given repetitive robot's route. The objective is to determine the starting times and durations of processing operations so as to minimize the cycle length. We reduce the problems to finding parametric critical paths in networks with varying arc lengths. In contrast to previously known methods, which solve these cyclic scheduling problems in cubic time, the parametric network approach solves the problems in $$O(m^2 {\text{ log }}m) $$ time, m being the problem size.