A minimalistic approach to appearance-based visual SLAM

This paper presents a vision-based approach to SLAM in indoor / outdoor environments with minimalistic sensing and computational requirements. The approach is based on a graph representation of robot poses, using a relaxation algorithm to obtain a globally consistent map. Each link corresponds to a relative measurement of the spatial relation between the two nodes it connects. The links describe the likelihood distribution of the relative pose as a Gaussian distribution. To estimate the covariance matrix for links obtained from an omni-directional vision sensor, a novel method is introduced based on the relative similarity of neighbouring images. This new method does not require determining distances to image features using multiple view geometry, for example. Combined indoor and outdoor experiments demonstrate that the approach can handle qualitatively different environments (without modification of the parameters), that it can cope with violations of the “flat floor assumption” to some degree, and that it scales well with increasing size of the environment, producing topologically correct and geometrically accurate maps at low computational cost. Further experiments demonstrate that the approach is also suitable for combining multiple overlapping maps, e.g. for solving the multi-robot SLAM problem with unknown initial poses

An adaptive appearance-based map for long-term topological localization of mobile robots

This work considers a mobile service robot which uses an appearance-based representation of its workplace as a map, where the current view and the map are used to estimate the current position in the environment. Due to the nature of real-world environments such as houses and offices, where the appearance keeps changing, the internal representation may become out of date after some time. To solve this problem the robot needs to be able to adapt its internal representation continually to the changes in the environment. This paper presents a method for creating an adaptive map for long-term appearance-based localization of a mobile robot using long-term and short-term memory concepts, with omni-directional vision as the external sensor

Omni-directional catadioptric vision for soccer robots

This paper describes the design of a multi-part mirror catadioptric vision system and its use for self-localization and detection of relevant objects in soccer robots. The mirror and associated algorithms have been used in robots participating in the middle-size league of RoboCup — The World Cup of Soccer Robots.This work was supported by grant PRAXIS XXI BM/21091/99 of the Portuguese Foundation for Science and Technolog

Toward an object-based semantic memory for long-term operation of mobile service robots

Throughout a lifetime of operation, a mobile service robot needs to acquire, store and update its knowledge of a working environment. This includes the ability to identify and track objects in different places, as well as using this information for interaction with humans. This paper introduces a long-term updating mechanism, inspired by the modal model of human memory, to enable a mobile robot to maintain its knowledge of a changing environment. The memory model is integrated with a hybrid map that represents the global topology and local geometry of the environment, as well as the respective 3D location of objects. We aim to enable the robot to use this knowledge to help humans by suggesting the most likely locations of specific objects in its map. An experiment using omni-directional vision demonstrates the ability to track the movements of several objects in a dynamic environment over an extended period of time

Designing Omni-Directional Mobile Robot Platform for Research

Machines, as a key workforce in manufacturing, mining, construction, are essential for industry, and socially. However, existing mobile robots’ designs do not provide enough mobility and maneuverability. This is one of the major factors that requires an improved design of mobile robot platform. This thesis is focused on designing an improved Omni-directional robot platform that has good mobility and maneuverability. To realize these conditions, a lot of criteria and constraints need to be considered in the design process. The conceptual design flows of this mobile robot are to satisfy the need of a mobile robot platform, establish Omni-directional mobile robot specifications followed by concept generation and concept selection. A full decomposition of Omni-directional mobile robot was done. This was followed by building a morphology chart to gather several ideas for those sub-functions of mobile robot. Combination of different types of sub-functions will generate several new Omni-directional mobile robot concepts. The concepts were drafted by using Three-dimensional (3-D) Computer Aided Designing SOLIDWORKS software. After concept generation, the concepts were evaluated by using weighted decision matrix method. The best concept was generated from 3-D design to get 2-D technical drawing and kinematics analysis. These analysis and results of the robot performance are presented in this thesi

Coordination and Control for a Team of Mobile Robots in an Unknown Dynamic Environment

This research presents a dual-level control structure for controlling a mobile robot or a group of robots to navigate through a dynamic environment (such as an object is moving in the workspace of a robot). The higher-level controller operates in cooperation with robot’s state estimation and mapping algorithm, Extended Kalman Filter – Simultaneous Localization and Mapping (EKFSLAM), and the lower-level controller (PID) controls the motion of the robot when it, encounters an obstacle, i.e., it reorients the robot to a predefined rebound angle and move it straight to maneuver around the obstacle until the robot is out of the obstacle range. The higher-level controller jumps in as soon as the robot is out of the obstacle range and moves the robot to the goal. The obstacle avoidance technique involves a novel approach to calculate the rebound angle. Further, the research implements the aforementioned technique to a Leader-Follower formation. Simulation and Experimental results have verified the effectiveness of the proposed control law