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The damping controller is popularly used in human-robot interaction to adapt the desired pose of the tool center via applied wrench (force and torque) by the human. However, the experimental identification of the suitable damping gain for the dynamical relationship between applied wrench and end-effector's velocity is an open problem. In addition, although the requirements of safe human-robot standards...
A modular approach for a robot has various advantages such as flexibility, re-configurability, and cost reduction. In this paper, we present a pick-and-place task with our modular manipulation system which is currently under development. The system consists of hardware platform, motion engine and task recognition engine and those elements are integrated for executing the task.
We present a framework for improving adaptability of Learning from Demonstration (LfD) strategy by combining the LfD and Sequential Quadratic Programming (SQP). The advantage of the LfD method is that it can find a motion planning solution that is suitable to a task in a short time. Although the method successfully generates a motion when a query point is similar to learned trajectories, it has a...
For several decades, swarm intelligence (SI), emergent collective intelligence of groups of simple agents, has been applied to diverse research areas including optimization problems. Particle swarm optimization, ant colony optimization, artificial bee colony algorithm are well-known examples, and many variants are proposed so far. Recently proposed cuckoo search is also one class of SI. It mimics...
In this paper, we present a path planning algorithm of a 7DOF manipulator with RRT(Rapidly-exploring Random Trees). The method presents a occlusion-free and collision-free path planning algorithm. First, we present a basics of RRT algorithm which is a basic searching method for a path planning of this paper. Second, the implementation of a occlusion-free path constraints is presented. Third, the collision-avoiding...
An evolutionary computational approach for a gait generation of a quadruped robot autonomously generates a gait that adapts in an environment. In this approach, a fitness function that measures a performance of the gait is defined and parameters are optimized by maximizing or minimizing the function with evolutionary computation algorithms. However the previous research only has considered the optimization...
Visual tracking has been a challenge in the computer vision field for a long time now because of the many uncertainties present. Ideally, a tracker should be able to withstand certain problems in tracking with minimal computation time. Some of the difficult situations are background clutter, partial occlusions and illumination changes to name a few. In this paper, a discriminative tracker using SURF...
Human detection is a challenging task in many fields because it is difficult to detect humans due to their variable appearance and posture. Furthermore, it is also hard to track the detected human because of their dynamic and unpredictable behavior. The evaluation speed of method also important as well as its accuracy. In this paper, we propose Simultaneous Detection and Tracking (SDAT) method using...
Human detection is a challenging task in many fields because it is difficult to detect humans due to their varying appearance and posture. The evaluation speed of the method is important as well as its accuracy. In this paper, we propose a novel method using Gaussian Particle Swarm Optimization (Gaussian-PSO) for human detection with the Histograms of Oriented Gradients (HOG) feature to achieve a...
A falling avoidance of biped robots is an important research topic to use the robot in a human life environment. In this paper, we propose a machine learning approach to falling detection and avoidacne for biped robots. Support Vector Machine (SVM) is used as the machine learning algorithm and it detects the falling state of the robot based on acceleration value of torso and center of pressure value...
This paper proposes a new algorithm for actor-critic method using online support vector regression(SVR), which can do incremental learning and automatically track variation of environment with time-varying characteristics. It gives good generalization properties to value function approximation and helps the critic converge fast. In addition, sample vectors in data set of the online SVR are used as...
Unlike animals and humans who are very adept at push recovery, humanoid robots push recovery is difficult for its high dimensional, non-linear, and hybrid features. Existed research results such like Capture points, provide several methods to recover from the push. However when a high magnitude push applies to the humanoid, existed methods are not enough to recover the robot. Towards this problem,...
In this paper, an improved Ant Colony Optimization (ACO) algorithm is proposed to solve path planning problems. These problems are to find a collision-free and optimal path from a start point to a goal point in environment of known obstacles. There are many ACO algorithms for path planning. However, it take a lot of time to get the solution and it is not to easy to obtain the optimal path every time...
A* algorithm can generate the optimized unique path if the cost function is well designed based on the given information. Especially for global path planning (GPP), A* is one of best solutions because GPP itself assume that a prior information. In this paper, classic A* algorithm is modified for outdoor military robot with risk and velocity map. For this purpose, we design velocity map using digital...
In this paper, experience repository based particle swarm optimization (ERPSO) is proposed for effectively applying particle swarm optimization (PSO) to evolutionary robotics application. The ERPSO uses a concept experience repository to store previous position and fitness of particles to accelerate convergence speed of PSO. We applied the ERPSO to find parameter of gait of a quadruped robot that...
In this paper, experience repository based particle swarm optimization (ERPSO) is suggested for effectively applying particle swarm optimization (PSO) to real life problems. The ERPSO uses a concept experience repository to store previous position and fitness of particles to accelerate convergence speed of PSO. The proposed method was compared with PSO variants in a three dimensional dynamic simulator...
In this paper, an improved ant colony optimization (ACO) algorithm is proposed to solve path planning problems. These problems are to find a collision-free and optimal path from a start point to a goal point in environment of known obstacles. There are many ACO algorithm for path planning. However, it take a lot of time to get the solution and it is not to easy to obtain the optimal path every time...
It is supposed that human and robot share living area in future. That time, the most important thing is security and safety of human. Robot have not injure human at any case. There are three ways for that. The first one is to control robot completely for fear that there is no emergency, which is almost impossible and dream of all engineers. The second one is to achieve smooth body like sponge. The...
This paper introduce a state classification method for detecting falling of biped robot. The method uses a support vector machine (SVM) to classify the state. The input vector for the SVM are a magnitude of acceleration, a position of center of pressure (CoP) in x and z axis, and tilt angles of torso relative to x and z axis. The input vector is based on sensor data that is measured from accelerometer...
This paper presents how to manager walking trajectories obtained by using multiobjective optimization algorithm. In the previous work, we have already obtained the multiple walking trajectories by using the multiobjective evolutionary algorithm. However, there was no guideline to manage and use these walking trajectories according to the given situations. In this paper, in order to make an extension...
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