Articulated robot

About: Articulated robot is a research topic. Over the lifetime, 4364 publications have been published within this topic receiving 52442 citations.

Optimal robot task scheduling based on genetic algorithms

Abstract: Industrial robots should perform complex tasks in the minimum possible cycle time in order to obtain high productivity. The problem of determining the optimum route of a manipulator's end effector visiting a number of task points is similar but not identical to the well-known travelling salesman problem (TSP). Adapting TSP to Robotics, the measure to be optimized is the time instead of the distance. In addition, the travel time between any two points is significantly affected by the choice of the manipulator's configuration. Therefore, the multiple solutions of the inverse kinematics problem should be taken into consideration. In this paper, a method is introduced to determine the optimum sequence of task points visited by the tip of the end effector of an articulated robot and it can be applied to any non-redundant manipulator. This method is based on genetic algorithms and an innovative encoding is introduced to take into account the multiple solutions of the inverse kinematic problem. The results show that the method can determine the optimum sequence of a considerable number of task points for robots up to six-degrees of freedom.

Motion planning for multiple mobile robots using dynamic networks

Abstract: A new motion planning framework is presented that enables multiple mobile robots with limited ranges of sensing and communication to maneuver and achieve goals safely in dynamic environments. To combine the respective advantages of centralized and de-centralized planning, this framework is based on the concept of centralized planning within dynamic robot networks. As the robots move in their environment, localized robot groups form networks, within which world models and robot goals can be shared. Whenever a network is formed, new information then becomes available to all robots in this network. With this new information, each robot uses a fast, centralized planner to compute new coordinated trajectories on the fly. Planning over several robot networks is decentralized and distributed. Both simulated and real-robot experiments have validated the approach.

Omni-directional mobile robot controller design by trajectory linearization

Abstract: In this paper, modeling and nonlinear controller design for an omnidirectional mobile robot are presented. Based on the robot dynamics model, a nonlinear controller is designed using the trajectory linearization control (TLC) method. Some simulation results of the controller are presented.

Physiological and subjective responses to articulated robot motion

Abstract: This paper describes the implementation and validation of a fuzzy inference engine for estimating human affective state in real-time, using robot motions as the stimulus. The inference engine was tested with 36 subjects. To the authors' knowledge, this paper reports the first such trial that measures affective response to human-scale physical robot motions for a statistically significant population. The results demonstrate that affective state arousal can be detected using physiological signals and the inference engine. Comparison of results between the two planners shows that subjects report less anxiety and surprise with the safe planner.

Optimal variable impedance control for a robot and its application to lifting an object with a human

Abstract: This paper describes a control method of a robot cooperating with a human. A task in which a robot and a human move an object cooperatively is considered To develop the force controller of the robot, the characteristics of human arm are investigated. The arm is forced to move along a trajectory in the experiment and the exerted force and the displacement are analyzed. It is found that the force characteristics of the human arm is regarded as an optimal damper with minimizing a cost function. Then, the model is implemented to a robot and the cooperation of the robot and a human operator is examined. The effectiveness of the derived model is evaluated and the experimental results show that the human moves the object supported by the robot with a minimum jerk trajectory. Next, the proposed control method is applied to a task in which a human and a robot lift an object cooperatively. The results show the effectiveness of the proposed control method.