Search results

Examines one of the main problems of mobile robot navigation: determining exactly where the robot is at all times. Describes the most important algorithm in localization: the extended Kalman filter. Looks at the simplest type of navigation using a system of fixed beacons in conjunction with a special sensor located on the vehicle and also the use of “natural beacons”. Discuss the problems of building and maintaining a map for the vehicle. Concludes that a complete solution to mobile vehicle localization is a long way off.

Stereo vision is an attractive perception technique for mobile robots navigation. Stereo matching is a crucial part of stereo vision and its precision dominates the precision of reconstruction. Based on a geometry constraint applicable to natural terrain, the purpose of this paper is to present a multi‐stage stereo matching algorithm to improve matching accuracy.

In the multi‐stage matching algorithm, points with larger intensity gradient are matched in earlier stages. Using several constraints and statistical means, information from earlier stages is utilized to assist in matching of later stages to improve matching accuracy.

The multi‐stage matching algorithm improves the matching accuracy of stereo pairs of natural terrain in various conditions.

The algorithm demonstrates advantages over area‐matching algorithm both in matching accuracy and computation efficiency. However, if used for real‐time navigation, it still needs the assistance of specialized hardware or window selection technique.

The algorithm is able to produce dense disparity maps of natural terrain with fairly high accuracy and can be used for the navigation of planetary rover or other outdoor mobile robots.

The paper provides a new approach to produce accurate and dense disparity maps of natural terrain, which laid the foundation for its use in outdoor mobile robots navigation.

Laser navigation without a reflector does not require setup of reflector markers at the scene and thus has the advantages of free path setting and flexible change. This technology has attracted wide attention in recent years and shows great potential in the field of automatic logistics, including map building and locating in real-time according to the environment. This paper aims to focus on the application of feature matching for map building.

First, an improved linear binary relation algorithm was proposed to calculate the local similarity of the feature line segments, and the matching degree matrix of feature line segments between two adjacent maps was established. Further, rough matching for the two maps was performed, and both the initial rotation matrix and the translation vector for the adjacent map matching were obtained. Then, to improve the rotation matrix, a region search optimization algorithm was proposed, which took the initial rotation matrix as the starting point and searched gradually along a lower error-of-objective function until the error sequence was nonmonotonic. Finally, the random-walk method was proposed to optimize the translation vector by iterating until the error-objective function reached the minimum.

The experimental results show that the final matching error was controlled within 10 mm after both rotation and translation optimization. Also, the algorithm of map matching and optimization proposed in this paper can realize accurately the feature matching of a laser navigation map and basically meet the real-time navigation and positioning requirements for an automated-guided robot.

A linear binary relation algorithm was proposed, and the local similarity between line segments is calculated on the basis of the binary relation. The hill-climbing region search algorithm and the random-walk algorithm were proposed to optimize the rotation matrix and the translation vector, respectively. This algorithm has been applied to industrial production.

This paper aims to propose an optimized overview of firefly algorithm (FA) over physical-natural impression of fireflies and its application in mobile robot navigation under the natural intelligence mechanism.

The brightness and luminosity are the decision variables in proposed study. The paper achieves the two major goals of robot navigation; first, the optimum path generation and, second, as an obstacle avoidance by co-in-centric sphere-based geometrical technique. This technique comprises the optimum path decision to objective function and constraints to paths and obstacles as the function of algebraic-geometry co-relation. Co-in-centric sphere is the proposed technique to correlate the constraints.

It is found that the present FA based on concentric sphere is suitable for efficient navigation of mobile robots at the level of optimum significance when compared with other approaches.

The paper introduces a novel approach to implement the FA for unknown and uncertain environment.

To present a stereo matching algorithm which satisfies the need of visual navigation on outdoor natural terrain for lunar rover or other mobile robots.

A feature‐assisted matching algorithm is presented to generate dense and accurate disparity map of natural terrain. Multi‐feature matching strategy produces reliable matching results for edge points. Disparity monotony constraint is derived and other geometrical constraints are introduced. With these constraints the edge‐matching results are used to limit the search region in area‐matching. As a result the algorithm produces dense disparity maps with fairly high accuracy and demonstrates advantages over straightforward area‐matching algorithm in improving matching accuracy.

With the help of several constraints, the feature‐assisted matching algorithm performs well in the matching of stereo image pairs of natural terrain.

The algorithm focus on improving the accuracy of stereo image pairs matching of natural terrain and computation complexity is not an important designing factor. Only with the assistance of special hardware or other technique can the algorithm be used for real‐time navigation.

The algorithm is able to produce dense disparity map of natural terrain with rather high accuracy and can be used for the navigation of lunar rover or other outdoor mobile robots.

The paper provides a new approach to produce accurate and dense disparity map of natural terrain.

Landmark‐based navigation of autonomous mobile robots or vehicles has been widely adopted in industry. Such a navigation strategy relies on identification and subsequent recognition of distinctive environment features or objects that are either known a priori or extracted dynamically. This process has inherent difficulties in practice due to sensor noise and environment uncertainty. This paper is to propose a navigation algorithm that simultaneously locates the robots and updates landmarks in a manufacturing environment. A key issue being addressed is how to improve the localization accuracy for mobile robots in a continuous operation, in which the Kalman filter algorithm is adopted to integrate odometry data with scanner data to achieve the required robustness and accuracy. The Kohonen neural networks have been used to recognize landmarks using scanner data in order to initialize and recalibrate the robot position by means of triangulation when necessary.

The purpose of this paper is to re-examine the important question of what is wrong with interactive voice response (IVR) system service by expanding a spatially informed conceptualisation of virtual navigation which recognises the experience of movement within and through space.

First, previous research on IVR systems is reviewed to highlight key themes to a service audience. Second, the metaphorical aspects of language used by the popular and trade press to describe IVR systems is examined. Usability and design issues are identified from previous research as a basis from reinterpreting them from a spatial perspective of navigation.

Both figurative and conceptual spatial metaphors are used to describe the IVR system as an enclosed physical space, within which customers enter, feel stuck, get lost, or try to escape from. The usability issues of human memory, linearity, and feedback, can be reinterpreted from a spatial perspective as a basis for explaining confusion and frustration with IVR systems.

Since the paper is conceptual, further research is needed to empirically investigate different types and features of IVR systems. The possible influence of age and culture upon the spatial nature of experience is especially interesting topics for future study.

The paper identifies the absence of space as an inherent limitation of IVR systems. It subsequently recommends that firms should provide spatial resources to support customer use of IVR systems, which is supported by the recent emergence of visual IVR.

The paper introduces the broader literature on IVR systems to the service field as a basis for raising awareness about this ubiquitous technological component of telephone-based service delivery. It applies and develops a highly abstract conceptual perspective to examine and interpret the representation and experience of IVR systems, as a basis for explaining the confusion, frustration, and dislike of them.

This study aims to present an automated guided logistics robot mainly designed for pallet transportation. Logistics robot is compactly designed. It could pick up the pallet precisely and transport the pallet up to 1,000 kg automatically in the warehouse. It could move freely in all directions without turning the chassis. It could work without any additional infrastructure based on laser navigation system proposed in this work.

Logistics robot should be able to move underneath and lift up the pallet accurately. Logistics robot mainly consists of two sub-robots, like two forks of the forklift. Each sub-robot has front and rear driving units. A new compact driving unit is compactly designed as a key component to ensure access to the narrow free entry of the pallet. Besides synchronous motions in all directions, the two sub-robots should also perform synchronous lifting up and laying down the pallet. Logistics robot uses a front laser to detect obstacles and locate itself using on-board navigation system. A rear laser is used to recognize and guide the sub-robots to pick up the pallet precisely within ± 5mm/1o in x-/yaw direction. Path planning algorithm under different constraints is proposed for logistics robot to obey the traffic rules of pallet logistics.

Compared with the traditional forklift vehicles, logistics robot has the advantages of more compact structure and higher expandability. It can realize the omnidirectional movement flexibly without turning the chassis and take zero-radius turn by controlling compact driving units synchronously. Logistics robot can move collision-free into any pallet that has not been precisely placed. It can plan the paths for returning to charge station and charge automatically. So it can work uninterruptedly for 7 × 24 h. Path planning algorithm proposed can avoid traffic congestion and improve the passability of the narrow roads to improve logistics efficiencies. Logistics robot is quite suitable for the standardized logistics factory with small working space.

This is a new innovation for pallet transportation vehicle to improve logistics automation.

The purpose of this article is to illustrate how sensors impart perceptive capabilities to robots. This is the second part of a two-part article. This second part considers positional awareness and sensing in the external environment, notably but not exclusively by autonomous, mobile robots.

Following a short introduction, this article first discusses positional sensing and navigation by mobile robots, including self-driving cars, automated guided vehicles, unmanned aerial vehicles (UAVs) and autonomous underwater vehicles (AUVs). It then considers sensing with UAVs and AUVs, and finally discusses robots for hazard detection. Brief concluding comments are drawn.

This shows that sensors based on a multitude of techniques confer navigational capabilities to mobile robots, including LIDARs, radar, sonar, imaging and inertial sensing devices. UAVs, AUVs and mobile terrestrial robots can be equipped with all manner of sensors to create detailed terrestrial and underwater maps, monitor air and water quality, locate pollution and detect hazards. While existing sensors are used widely, many new devices are now being developed to meet specific requirements and to comply with size, weight and cost restraints.

The use of mobile robots is growing rapidly, and this article provides a timely account of how sensors confer them with positional awareness and allow them to act as mobile sensing platforms.