Crowdsourcing Swarm Manipulation Experiments: A Massive Online User Study with Large Swarms of Simple Robots

Micro- and nanorobotics have the potential to revolutionize many applications including targeted material delivery, assembly, and surgery. The same properties that promise breakthrough solutions---small size and large populations---present unique challenges to generating controlled motion. We want to use large swarms of robots to perform manipulation tasks; unfortunately, human-swarm interaction studies as conducted today are limited in sample size, are difficult to reproduce, and are prone to hardware failures. We present an alternative. This paper examines the perils, pitfalls, and possibilities we discovered by launching SwarmControl.net, an online game where players steer swarms of up to 500 robots to complete manipulation challenges. We record statistics from thousands of players, and use the game to explore aspects of large-population robot control. We present the game framework as a new, open-source tool for large-scale user experiments. Our results have potential applications in human control of micro- and nanorobots, supply insight for automatic controllers, and provide a template for large online robotic research experiments.Comment: 8 pages, 13 figures, to appear at 2014 IEEE International Conference on Robotics and Automation (ICRA 2014

Ball positioning in robotic billiards: a nonprehensile manipulation-based solution

The development and testing of a robotic system to play billiards is described in this paper. The last two decades have seen a number of developments in creating robots to play billiards. Although the designed systems have uccessfully incorporated the kinematics required for gameplay, a system level approach needed for accurate shot- making has not been realized. The current work considers the different aspects, like machine vision, dynamics, robot design and computational intelligence, and proposes, for the first time, a method based on robotic non-prehensile manipulation. High-speed video tracking is employed to determine the parameters of balls dynamics. Furthermore, three-dimensional impact models, involving ball spin and friction, are developed for different collisions. A three degree of freedom manipulator is designed and fabricated to execute shots. The design enables the manipulator to position the cue on the ball accurately and strike with controlled speeds. The manipulator is controlled from a PC via a microcontroller board. For a given table scenario, optimization is used to search the inverse dynamics space to find best parameters for the robotic shot maker. Experimental results show that a 90% potting accuracy and a 100–200 mm post-shot cue ball positioning accuracy has been achieved by the autonomous system

Spartan Daily, November 18, 2014

Volume 143, Issue 33https://scholarworks.sjsu.edu/spartandaily/1532/thumbnail.jp

Goal-oriented Dialogue Policy Learning from Failures

Reinforcement learning methods have been used for learning dialogue policies. However, learning an effective dialogue policy frequently requires prohibitively many conversations. This is partly because of the sparse rewards in dialogues, and the very few successful dialogues in early learning phase. Hindsight experience replay (HER) enables learning from failures, but the vanilla HER is inapplicable to dialogue learning due to the implicit goals. In this work, we develop two complex HER methods providing different trade-offs between complexity and performance, and, for the first time, enabled HER-based dialogue policy learning. Experiments using a realistic user simulator show that our HER methods perform better than existing experience replay methods (as applied to deep Q-networks) in learning rate

Asian Roboticism: Connecting Mechanized Labor to the Automation of Work

Abstract This article reconsiders the present-day automation of work and its transformation of who we are as humans. What has been missing from this important conversation are the social meanings surrounding Asian roboticism or how Asians have already been rendered as “robotic” subjects and labor. Through this racial gendered trope, I assess whether industrial automation will lessen, complicate, or exacerbate this modern archetype. By looking at corporate organizational practices and public media discourse, I believe that Asian roboticism will not simply vanish, but potentially continue to affect the ways such subjects are rendered as exploitable alienated robots without human rights or status

Physically Interactive Robogames: Definition and Design Guidelines

There is evidence that people expects to be able to play games with autonomous robots, so that robogames could be one of the next killer ap- plications for Robotics. Physically Interactive RoboGames (PIRG) is a new application field where autonomous robots are involved in games requiring physical interaction with people. Since research in this field is moving its first steps, definitions and design guidelines are still largely missing. n this paper, a definition for PIRG is proposed, together with guidelines for their design. Physically Interactive, Competitive RoboGames (PICoRG) are also introduced. They are a particular kind of PIRG where human players are involved in a challenging, highly interactive and competitive game activity with autonomous robots. The development process of a PICoRG, Jedi Trainer , is presented to show a practical application of the proposed guidelines. The game has been successfully played in different unstructured environments, by general public; feedback is reported and analysed