Directional drilling is a method to bore toward a desired path. For control of directional drilling, the information about underground localization is important. However, in underground environment, GPS signal is unre...
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ISBN:
(纸本)9783319168418;9783319168401
Directional drilling is a method to bore toward a desired path. For control of directional drilling, the information about underground localization is important. However, in underground environment, GPS signal is unreachable and wireless beacon system is useless. Conventional researches focused on the methods based on IMU (Inertial Measurement Unit), but vibration of drilling and distortion of magnetic fields interfere with the IMU measurement. In this paper, a new underground localization algorithm for directional drilling using graph SLAM (simultaneous localization and mapping) and magnetic fields in backward travel is proposed. The proposed algorithm records magnetic fields in forward travel and optimizes the poses using the graph SLAM by matching magnetic fields in backward travel. The proposed algorithm is verified by simulations.
Model checking is a technique to perform a formal verification process that allows a system to have robustness and correctness. In a given system model as a Finite State Machine (FSM), model checker explores all possi...
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ISBN:
(纸本)9783319168418;9783319168401
Model checking is a technique to perform a formal verification process that allows a system to have robustness and correctness. In a given system model as a Finite State Machine (FSM), model checker explores all possible states in brute-force manner. In this paper, we apply this technique to a training system, which teaches a humanoid soccer robot how to intercept a ball that is passed from other players, to verify that the system is failure-safe in a given requirements. Several Computation Tree Logic (CTL) properties to define a critical or potential situation are specified based on the functionality of the system. We show the results of the given properties using NuSMV, a symbolic model checker introduced by Carnegie Mellon University.
Simultaneous localization and mapping (SLAM) is becoming one of the most attractive research focuses of robot control and visual processing. In this paper, robot performs a SLAM mission in an unknown and structured in...
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ISBN:
(纸本)9783319168418;9783319168401
Simultaneous localization and mapping (SLAM) is becoming one of the most attractive research focuses of robot control and visual processing. In this paper, robot performs a SLAM mission in an unknown and structured indoor environment with the Microsoft XBOX Kinect obtaining visual and depth information. The line features of the object as mapping elements are extracted from visual images, and according to the extraction result, the distance between line features of the object and the robot can be obtained to portray the object edge onto the map in 2D, and the distance is provided by depth data from the Kinect. Meanwhile the robot motion model is created for the trajectory plan. A method using the extended Kalman filter (EKF) is applied to provide a pose estimate for the robot motion trajectory. The SLAM strategy is demonstrated in simulation and experimental environment.
Human-like gaze control of robots is essential for natural human robot interaction (HRI), and thus it is necessary to identify the gaze control factors that affect human gaze. In this paper, the gaze control factors a...
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ISBN:
(纸本)9783319168418;9783319168401
Human-like gaze control of robots is essential for natural human robot interaction (HRI), and thus it is necessary to identify the gaze control factors that affect human gaze. In this paper, the gaze control factors are derived inductively from the observation of human scanpaths. Human scanpaths are measured from movie clips and are transformed into vector-based representation that contains spatio-temporal information. The transformed scanpaths are compared to find the most common scanpath. The selected scanpath is analyzed to identify the gaze control factors. The derived factors are anticipation, knowledge, and attractions in a static image such as salient regions, humans, objects, and center of visual inputs.
This paper describes a simple and effective system for counting the number of objects that move through a region of interest. In this work, I focus on the problem of counting the number of people that are entering or ...
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ISBN:
(纸本)9783319168418;9783319168401
This paper describes a simple and effective system for counting the number of objects that move through a region of interest. In this work, I focus on the problem of counting the number of people that are entering or leaving an event. I design a pedestrian counting system that uses a dense optical flow field to calculate the integral of the optical flow in a video sequence. The only parameter used in the system is the the estimated integral flow for a single person. This parameter can be easily calculated from a short training sequence. Empirical evaluations show that the system is able to provide accurate estimates even for complex sequences in real-time. The described system won 2nd place in the pedestrian counting computer vision competition at the IEA-AIE 2014 conference.
The most important issue for intelligent mobile robot development is the ability to navigate autonomously in the environment to complete certain tasks. Thus, the indoor localization problem of a mobile robot has becom...
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The most important issue for intelligent mobile robot development is the ability to navigate autonomously in the environment to complete certain tasks. Thus, the indoor localization problem of a mobile robot has become a key component for real applications. In general, two categories of mobile robot localization technique are identified: one is robot pose tracking, and the other is robot global localization. In pose tracking problems such as the simultaneous localization and mapping (SLAM) process, the robot has to find its new pose using the observed landmarks or features in its knowledge base of its previous observations. In global localization methodology, a robot does not have knowledge of its previous pose. It has to find its new pose directly in the environment, such as by using a global positioning system (GPS). On the other hand, an artificial beacon-based localization technique, such as the received signal strength indicator (RSSI), causes higher pose uncertainty. However, the artificial beacon can provide a good initial reference for robot position mapping. The gyrocompass of a mobile robot is suited for short-term dead-reckoning. Also the RGB-D camera of a mobile robot can record meaningful features or landmarks in 3D space. The purpose of this work is to fuse the advantages of these sensors via strategy control by a particle filter to enhance the estimation accuracy of indoor mobile robot localization.
Humanoid robot requires a robust prevention system against external disturbances to protect itself from falling to the ground and to perform its tasks completely. In this paper, a Falling Prevention System for humanoi...
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ISBN:
(纸本)9783319168418;9783319168401
Humanoid robot requires a robust prevention system against external disturbances to protect itself from falling to the ground and to perform its tasks completely. In this paper, a Falling Prevention System for humanoid robot is proposed to avoid falling from the disturbances, and helps humanoid robot recover its balance from external force by taking a step. The algorithm for the Falling Prevention System consists of two processes. First, humanoid robot can perceive whether it is falling or not by using an IMU sensor, and if falling, the center of mass (CoM) and swinging leg trajectories are calculated for the robot to take a step. The CoM and swinging leg trajectories are also used to acquire all joint angles of lower body by inverse kinematics. Furthermore, designed foot trajectory helps humanoid robot minimize its yawing moment. Next, mass-spring-damper system for the robot's legs is modeled to reduce large impact force from the ground. The effectiveness of the proposed method is demonstrated through computer simulations for a humanoid robot.
This paper we introduce a torque feedback control (TFC) model to estimate pressure of the hand on a 4-DOF robotic arm of Betty, a humanoid robot. Based on several preliminary experiments of different stroke patterns, ...
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ISBN:
(纸本)9783319168418;9783319168401
This paper we introduce a torque feedback control (TFC) model to estimate pressure of the hand on a 4-DOF robotic arm of Betty, a humanoid robot. Based on several preliminary experiments of different stroke patterns, we measured and analysed the torque replies of Betty's servos in order to model the torque feedback. We developed a robust humanoid system to create sketch like drawing with limited hardware which has no force sensor but basic torque feedback from servos to estimate pressure apply on drawing pad. We investigated the efficiency of using the TFC in the drawing task based on several different stroke patterns. The experimental results indicate that the TFC model successfully corrected the errors during the drawing task.
This research explores a new hybrid evolutionary learning methodology for multi-behaviour robot control. The new approach is an extension of the Fuzzy Genetic Network Programming algorithm with Reinforcement learning ...
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ISBN:
(纸本)9783319168418;9783319168401
This research explores a new hybrid evolutionary learning methodology for multi-behaviour robot control. The new approach is an extension of the Fuzzy Genetic Network Programming algorithm with Reinforcement learning presented in [1]. The new learning system allows for the utilisation of any pre-trained intelligent systems as processing nodes comprising the phenotypes. We envisage that compounding the GNP with more powerful processing nodes would extend its computing prowess. As proof of concept, we demonstrate that the extended evolutionary system can learn multi-behaviours for robots by testing it on the simulated Mirosot robot soccer domain to learn both target pursuit and wall avoidance behaviours simultaneously. A discussion of the development of the new evolutionary system is presented following an incremental order of complexity. The experiments show that the proposed algorithm converges to the desired multi-behaviour, and that the obtained system accuracy is better than a system that does not utilise pre-trained intelligent processing nodes.
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