From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

The control of a biped humanoid is a challenging task due to the hard-to-stabilize dynamics. Walking reference trajectory generation is a key problem. Linear Inverted Pendulum Model (LIPM) and Zero Moment Point (ZMP) Criterion-based approaches in stable walking reference generation are reported. In these methods, generally, the ZMP reference during a stepping motion is kept fixed in the middle of the supporting foot sole. This kind of reference generation lacks naturalness, in that the ZMP in the human walk does not stay fixed, but it moves forward under the supporting foot. This paper proposes a reference generation algorithm based on the LIPM and moving support foot ZMP references. The application of Fourier series approximation simplifies the solution, and it generates a smooth ZMP reference. A simple inverse kinematics-based joint space controller is used for the tests of the developed reference trajectory through full-dynamics 3D simulation. A 12-DOF biped robot model is used in the simulations. Simulation studies suggest that the moving ZMP references are more energy efficient than the ones with fixed ZMP under the supporting foot. The results are promising for implementations.

/pdf/natural-zmp-trajectories-for-biped-robot-reference-4fzexxp14q.pdf

Natural ZMP Trajectories for Biped Robot Reference Generation

Autonomous mobile robots are becoming more prominent in recent time because of their relevance and applications to the world today. Their ability to navigate in an environment without a need for physical or electro-mechanical guidance devices has made it more promising and useful. The use of autonomous mobile robots is emerging in different sectors such as companies, industries, hospital, institutions, agriculture and homes to improve services and daily activities. Due to technology advancement, the demand for mobile robot has increased due to the task they perform and services they render such as carrying heavy objects, monitoring, search and rescue missions, etc. Various studies have been carried out by researchers on the importance of mobile robot, its applications and challenges. This survey paper unravels the current literatures, the challenges mobile robot is being faced with. A comprehensive study on devices/sensors and prevalent sensor fusion techniques developed for tackling issues like localization, estimation and navigation in mobile robot are presented as well in which they are organised according to relevance, strengths and weaknesses. The study therefore gives good direction for further investigation on developing methods to deal with the discrepancies faced with autonomous mobile robot.

/pdf/a-review-on-challenges-of-autonomous-mobile-robot-and-sensor-yw1sv39uan.pdf

A Review on Challenges of Autonomous Mobile Robot and Sensor Fusion Methods

Robot navigation is an indispensable component of any mobile service robot. Many path planning algorithms generate a path which has many sharp or angular turns. Such paths are not fit for mobile robot as it has to slow down at these sharp turns. These robots could be carrying delicate, dangerous, or precious items and executing these sharp turns may not be feasible kinematically. On the contrary, smooth trajectories are often desired for robot motion and must be generated while considering the static and dynamic obstacles and other constraints like feasible curvature, robot and lane dimensions, and speed. The aim of this paper is to succinctly summarize and review the path smoothing techniques in robot navigation and discuss the challenges and future trends. Both autonomous mobile robots and autonomous vehicles (outdoor robots or self-driving cars) are discussed. The state-of-the-art algorithms are broadly classified into different categories and each approach is introduced briefly with necessary background, merits, and drawbacks. Finally, the paper discusses the current and future challenges in optimal trajectory generation and smoothing research.

https://www.mdpi.com/1424-8220/18/9/3170/pdf

Path Smoothing Techniques in Robot Navigation: State-of-the-Art, Current and Future Challenges

Fuzzy logic-based real-time robot navigation in unknown environment with dead ends

Path searching algorithm is one of the main topics in studies on path planning. These algorithms are used to avoiding obstacles and find paths from starting point to target point. There are dynamic problems that must be addressed when these paths are applied in real environments. In order to be applicable in actual situations, the path must be a smooth path. A smooth path is a path that maintains continuity. Continuity is decided by the differential values of the path. In order to be G2 continuous, the secondary differential values of the path must be connected throughout the path. In this paper, the interpolation method is used to construct continuous paths. The quadratic polynomial interpolation is a simple method for obtaining continuous paths about three points. The proposed algorithm makes a connection of three points with curves and the proposed path is rotated using the parametric method in order to make the path optimal and smooth. The polynomials expand to the next three points and they merge int...

https://journals.sagepub.com/doi/pdf/10.5772/57340

A G2 Continuous Path-smoothing Algorithm Using Modified Quadratic Polynomial Interpolation

Given a certain target point, the mobile robot's navigation could be mainly considered about two areas, 'how fast and accurate' and 'how safe'. Such problems regarding the velocity and stability have close relationship with the path in which the mobile robot navigates. Therefore, in this paper, considering the surrounding environment, the path planning was conducted to ensure stable navigation of the mobile robot for two main parts. First, the shortest path and the feature point for the global path planning was chosen by utilizing cell decomposition method off-line computation. Second, to control the movement and path between the feature points, Potential field method, which acutely responds to the surrounding environment on-line computation, is used. In order to detect the given path and avoid obstacles, the navigation algorithm was composed by using two fuzzy logic control.

Path planning and navigation for autonomous mobile robot

In this paper, a method of designing an adaptive controller is proposed to solve some problems in model reference adaptive control (MRAC) for nonlinear plants. The MRAC was originally designed for the unknown plant which should be linear and completely disturbance free. Practically, since real plants have nonlinearities, such as disturbances and unmodelled dynamics, the performance of the controller is worsened. This paper describes an error feedback model which is a reference model with the output error feedback, for improving robustness and stability to nonlinear characteristics. The proposed model can be used for MRAC using the measurable output of the plant and the states of the proposed model. Experiments on an SR (switched reluctance) motor have been done in order to illustrate the validity of the proposed controller.

An error feedback model based adaptive controller for nonlinear systems

This paper is concerned with a balancing motion formulation and control of the ZMP (zero moment point) for a biped walking robot that has a balancing weight of an inverted pendulum. The original dynamic stability equation of a walking robot is nonlinear; because it's balancing weight is an inverted pendulum type. The stabilization equation of a biped walking robot is modeled as a linearized non-homogeneous second order differential equation with boundary conditions. With the FDM (finite difference method) solution of the linearized differential equation, a trajectory of balancing weight can be directly calculated. Furthermore, it makes that possible input the desired ZMP or ZMP trajectory for various gait, situation and complex motion. Also, it can be easily approximated that a balancing range or motion when some link parameters are changed; especially a balancing mass is changed. In this paper, the simulator with a balancing weight of an inverted pendulum is programmed to get and calculate the desired ZMP and the actual ZMP. The operating program is developed for a real biped walking robot IWRIII-IP. Walking of 6 steps will be simulated and experimented with a real biped walking robot. This balancing system will be applied to a biped humanoid robot, which consist legs and upper body, at future work.

Stability experiment of a biped walking robot with inverted pendulum

Path planning is essential for the autonomous navigation of mobile robots. Researchers have been working on ensuring the safe navigation of mobile robots; however, it is impossible to secure the absolute safety of a mobile robot without environmental information. Nevertheless, passive safety of a mobile robot can be secured. With the aim of ensuring safe path planning of a mobile robot, a safety space is proposed in this work by using the parameters of stopping distance and hazard point. Mobile robots should formulate path plans to bypass crossroads or corner areas where their field of view is limited, and they should also be capable of reducing their movement speed to secure safe driving. We demonstrate through extensive simulations that the developed SGPP (safe global path planning) method outperforms the classical A * and PRM (probabilistic roadmap) algorithms. It improves the navigation time and length of the robot path in comparison to the PRM algorithm and reduces the navigation time by up to 26% compared to the classical A * algorithm for safe navigation. In addition, results of an experiment conducted on a real robot show that the SGPP method finds a safe path with limited velocity for safe navigation.

http://koreascience.or.kr:80/article/JAKO201635551194441.pdf

Uk-Youl Huh

Papers

A G2 Continuous Path-smoothing Algorithm Using Modified Quadratic Polynomial Interpolation

Path planning and navigation for autonomous mobile robot

An error feedback model based adaptive controller for nonlinear systems

Stability experiment of a biped walking robot with inverted pendulum

Path Planning for Autonomous Mobile Robot Based on Safe Space