Lightweight design leads to the unwanted vibration of industrial robot manipulators. Input Shaping (IS) has been proven to be an effective vibration suppression method. However, applying IS to suppress the vibration of industrial robots faces a challenging problem: time-varying dynamics. To address the time-varying dynamics of robot manipulators, this paper presents a novel and practical solution to vibration suppression based on Time-Varying Input Shaping Technology (TVIST). Our focus in this paper is to develop a practical implementation strategy that can be applied in discrete time. A Fractional Delay Finite Impulse Response filter is employed to design and implement TVIST. This solution makes TVIST more useful in practice because it can be combined with online and discrete-time trajectory generation. It can also be implemented in combination with position control using feed-forward velocity and torque. The performance of the new approach is validated through experimental implementation on a lightweight robot from Universal Robots A/S. Experimental results are analyzed to demonstrate significant vibration suppression and increased productivity of the robot with the proposed solution. The proposed method can be extended to the vibration suppression of other types of industrial robotic manipulators with serial links as well as other time-varying dynamic systems.

Flexibility commonly exists in the joints of many industrial robots due to the elasticity of the lightweight strain-wave type transmissions being used. This leads to a dynamic time-varying displacement between the position of the drive actuator and that of the driven link. Furthermore, the joint flexibility changes with time due to the material slowly being worn off at the gear meshing. Knowing the stiffness of the robot joints is of great value, e.g. in the design of new model-based feedforward and feedback controllers, and for predictive maintenance in the case of gearing unit failure. In this paper, we address on-line estimation of robot joint stiffness using a recursive least squares strategy based on a parametric model taking into account the elastic torques' nonlinear dependency on transmission deformation. Robustness is achieved in the presence of measurement noise and in poor excitation conditions. The method can be easily extended to general classes of serial-link multi-degree-of-freedom robots. The estimation technique uses only feedback signals that are readily available on Universal Robots' e-Series manipulators. Experiments on the new UR5e manipulator demonstrate the effectiveness of the proposed method.

This paper presents a new method to generate vibration free rest-to-rest (RTR) trajectories for configuration dependent dynamic systems, such as robots, cranes or machine tools. The new method named 3-Segmented Input Shaping is based on a combination of the widely known Input Shaping method and a new trajectory segmentation strategy for piece wise shaping of the trajectory. The new segmentation strategy facilitates the capability of accounting for variations in system dynamics during motion by shaping acceleration and deceleration profiles with individual frequencies. In this paper the new segmentation strategy is used in combination with the bang-coast-bang (BCB) trajectory. The generated trajectories are described in closed form, hence requires no optimization and thereby provides strong computational performance. The new method is verified by numerical simulations and detailed analysis and shows great potential in vibration-free RTR trajectory generation for systems with configuration dependent dynamics.

A modular robot consists of a set of mechatronic modules that can be connected in many different ways, which makes it possible to build robots of many different shapes from the same basic set of modules. The main contribution of this work is an algorithm that, given the parameters of a module and the number of modules, efficiently can calculate how many different configurations and shapes can be built. These numbers are important because the first is a measure of the self-reconfigurability and the second, given there is a relationship between form and function, the versatility of a modular robot. As an experimental contribution, we enumerate the configuration and shape spaces of square, two-dimensional modules with all possible connector configurations. We proceed to three dimensions and enumerate the spaces of the theoretically interesting sliding cube module, and the M-TRAN and SuperBot modules. Several observations are made, an important one is that the shape spaces of the two physical modules are large even for a small number of modules (103 different shapes using 3 modules). This implies that it is not the lack of shape diversity that holds these modular robots back from being versatile. A result that suggests that if modules are designed right, versatility can potentially be reached even with few modules, which is contrary to the common belief in the community that more is better.

Online games are a rapidly growing Internet application. In order to run a successful online game, game companies and game infrastructure providers must properly manage game workloads and content so that they can maximize player satisfaction while minimizing their own costs. Toward this end, this paper provides a comprehensive, long-term analysis of several popular online games and their players using one of the richest data sets available for online games.

Generic simulation platforms such as player/stage are an essential tool in mobile robotics, but until now no similar platforms have been available for the field of self-reconfigurable robots. We here present a generic simulation platform for modular, self-reconfigurable robots: the unified simulator for self-reconfigurable robots (USSR). USSR is based on a physics engine, allowing simulation of both self-reconfiguration and dynamic interaction with the environment. The simulator is implemented as a framework that provides numerous components that can be combined to form new or existing modular robots, allowing easy experimentation: USSR currently includes support for the ATRON, Odin, and M-TRAN modular robots.

In this paper we present a 2D meta-module for the ATRON robot, which simplifies the motion constraints significantly. The motion capabilities of the new meta-module is similar to that of previous sliding cube style modules with the addition of one extra action, which is shown to improve the motion capabilities of the modules greatly. In general our work shows that if three simple actions, which is implemented by our proposed meta-module, is implemented by a self-reconfigurable robot module or meta-module then the control of the robot will be simple. The improved motion capabilities allow us to use offline planning for large groups consisting of hundreds of meta- modules. The simple motion constraints of the meta-module further allows us to implement a distributed cluster flow locomotion gait, with the interesting property that the group of meta-modules self-organizes into a shape that makes the locomotion efficient.

This paper presents a comparison between two different algorithms for self-reconfiguration planning on modular self-reconfigurable robots. The two algorithms are A* and RRT-Connect. A* has often been used for self-reconfiguration planning on different systems, but so far no work has been done to show that A* is an optimal or even a good choice for this task. The RRT-connect algorithm is adopted from traditional robot motion planning and is easily adapted to self-reconfiguration planning. The results show that RRT-connect is significantly faster than A* for difficult self-reconfiguration problems. In most cases RRT-connect generates longer paths that A* it is, however, possible to optimize the paths from RRT-connect by a simple and efficient method such that the difference is negligible

Behavioural experiments with crickets show that female crickets respond only to the male calling songs with a syllable rate within a specific interval, further it has been discovered that their response is independent of the duty-cycle of the song. Previously a neural control model was posed, which was able to explain how the selectivity of songs with syllable rates within a certain bandwidth could be obtained. The model explained why female crickets' response to calling songs was invariant to the duty-cycle of the songs. Here, we propose a new neural model, which is able also to account for the selectivity of a specific syllable rate and is invariant to the song duty-cycle. Implementing it on a small, mobile robot and using an analog electronic model of the peripheral auditory morphology of the female cricket as the sensor test the new model. The robot is placed under the same experimental conditions as the real crickets and it responds with phonotaxis to synthetic calling songs with syllable rates within a certain bandwidth similar to crickets. Further, the robot performs phonotaxis to songs with a syllable rate within the correct bandwidth independently of the duty-cycle of the song.