Martin Dekan

VFH*TDT (VFH* with Time Dependent Tree)

A new modifications of VFH+ and VFH* (Vector Field Histogram) methods are presented in the paper. The features of the histogramic algorithms are generally improved and also using a potential of advanced sensors such as laser scanners is enabled. The main focus of the work is an introduction of modifications that provides collision-free navigation in environments with moving obstacles. For this purpose, a new approach in creating a look-ahead tree is proposed. All new modifications are analyzed and experimentally verified. The results obtained using conventional and modified methods have been compared. Experiments have demonstrated the validity and the technical feasibility of the proposed methods.

Moving obstacles detection based on laser range finder measurements

The objective of this article is to propose data processing from laser range finder that will provide simple, fast, and reliable object recognition including moving objects. The whole method is based on four steps: segmentation, simplification, correspondence between consequent measurements, and object classification. Segmentation uses raw data from laser range finder and it is significant in logical connection of related segments. The most important step is simplification which provides data reduction and acceleration of object classification. The output of simplification is an object represented by significant points. Correspondence between consequent measurements is based on kd-tree nearest neighborhood search. The object is then classified by its spatial changes. These changes are evaluated by position of correspondent significant points. Input of proposed procedure is a probabilistic model of laser range finder. In this article, versatile probabilistic model of Hokuyo URM-30 LX was used. The method was verified by simulations and by tests in real environment. The results show that proposed method is reliable and with small modifications (of parameters), it is usable with any other planar laser range finder.

Optimization of Robotic Arm Trajectory Using Genetic Algorithm

Abstract The paper presents a genetic algorithm - based design approach of the robotic arm trajectory control with the optimization of various criterions. The described methodology is based on the inverse kinematics problem and it additionally considers the minimization of the operating-time, and/or the minimization of energy consumption as well as the minimization of the sum of all rotation changes during the operation cycle. Each criterion evaluation includes the computationally demanding simulation of the arm movement. The proposed approach was verified and all the proposed criterions have been compared on the trajectory optimization of the industrial robot ABB IRB 6400FHD, which has six degrees of freedom.

Optimal Navigation for Mobile Robot in Known Environment

Optimal navigation is a subset of robot navigation in an environment. It is also known as a path planning. The aim of the optimal navigation is to choose optimal path between the initial state and the desired state of the robot. There are many methods how to choose the optimal path. In this article A* algorithm was chosen, because it is widely applied. The main idea was to propose an algorithm, which is able to select the optimal path in a typical indoor environment. Despite that our real robot uses metric maps and A* algorithm is primarily designated for the topological maps, it was verified in the experiments that this algorithm can be used for off-line path planning.

Multi-Robot System for Mapping of the Unknown Environment

The aim of this article is proposal and implementation of the multi-robot system for mapping of the unknown environment. For the localization of each robot, simple odometry was used. Navigation of the robots is based on algorithm similar to bug algorithms. Communication between robots is based on polling. The system was implemented on the platform iRobot Create. Practical experiments have proven that multi-robot system for mapping of the unknown environment is faster and more reliable than single robot system.

Using Octree Maps and RGBD Cameras to Perform Mapping and A* Navigation

Ability to explore unknown environments and ability to successfully navigate in these environments are two key abilities of any truly autonomous mobile robot. In this article, an efficient implementation of mapping and navigation using only RGBD cameras is presented. The map created by Visual SLAM techniques is converted into Octree structure, and successful A* Navigation between two points in 3D is performed. The created mapping system is able to operate in real-time even on small mobile robot and can be easily extended with new state-of-the art techniques. Proposed way of octree encoding, due to its minimum storage requirements, enables efficient distribution of map between multiple robots over the network. Presented path-planning method with its optimizations runs in sufficient time even in higher resolution maps.

Detection of Welds in Automated Welding

This article deals with automated welding conceived as a robotic welding cell. Laser scanners used in automated welding are described in the main part of the article. Then, the control scheme of the robotic welding is defined. Several simple algorithms are proposed for the data processing. Emphasis in these algorithms has been placed on simplicity, so that they can run online. Algorithms have been verified on several scenarios.

Control of overhead crane based on Lyapunov approach to fuzzy controller synthesis

The subject of the paper is synthesis of a robust controller of the load swing during motion of overhead cranes. The approach implements fuzzy partition to the state variables. Stability is secured by employing the Lyapunov theory. The proposed methodology is the most appropriate for the presented problem since exact knowledge about the plant parameters is not needed. Numerical tests show the feasibility of the control scheme.

Vector Field Histogram* with look-ahead tree extension dependent on time variable environment:

The article deals with a novel approach to reactive navigation. A proposed reactive navigation is based on the Vector Field Histogram (VFH) method, which is easily modifiable. The biggest advantage of the proposed method is that it allows the robot to avoid static as well as moving obstacles in an unknown environment in a more effective way and without the need of switching any algorithm or the robot’s behaviour. Moreover, the proposed extension allows the avoidance of several moving obstacles in real time. The article contains three proposed improvements of the original VFH* method: representation of moving objects, look-ahead tree improvements and approach to criterion function. The method is verified by several experiments in various scenarios, which include few static and moving obstacles.

Foundations of Visual Linear Human–Robot Interaction via Pointing Gesture Navigation

This paper presents a human–robot interaction method for controlling an autonomous mobile robot with a referential pointing gesture. A human user points to a specific location, robot detects the pointing gesture, computes its intersection with surrounding planar surface and moves to the destination. A depth camera mounted on the chassis is used. The user does not need to wear any extra clothing or markers. The design includes necessary mathematical concepts such as transformations between coordinate systems and vector abstraction of features needed for simple navigation, which other current research works misses. We provide experimental evaluation with derived probability models. We term this approach “Linear HRI” and define 3 laws of Linear HRI.