Interactive fiction | EPFL Graph Search

Interactive fiction, often abbreviated IF, is software simulating environments in which players use text commands to control characters and influence the environment. Works in this form can be understood as literary narratives, either in the form of interactive narratives or interactive narrations. These works can also be understood as a form of video game, either in the form of an adventure game or role-playing game. In common usage, the term refers to text adventures, a type of adventure game where the entire interface can be "text-only", however, graphic text adventures still fall under the text adventure category if the main way to interact with the game is by typing text. Some users of the term distinguish between interactive fiction, known as "Puzzle-free", that focuses on narrative, and "text adventures" that focus on puzzles. Due to their text-only nature, they sidestepped the problem of writing for widely divergent graphics architectures. This feature meant that interactive fiction games were easily ported across all the popular platforms at the time, including CP/M (not known for gaming or strong graphics capabilities). The number of interactive fiction works is increasing steadily as new ones are produced by an online community, using freely available development systems. The term can also be used to refer to analogue versions of literary works that are not read in a linear fashion, known as gamebooks, where the reader is instead given choices at different points in the text; these decisions determine the flow and outcome of the story. The most famous example of this form of printed fiction is the Choose Your Own Adventure book series, and the collaborative "" format has also been described as a form of interactive fiction. The term "interactive fiction" is sometimes used also to refer to visual novels, a type of interactive narrative software popular in Japan. Text adventures are one of the oldest types of computer games and form a subset of the adventure genre.

Learning From Demonstration and Interactive Control of Variable-Impedance to Cut Soft Tissues

Aude Billard, Rui Wu

In this article, we propose an approach to extract variable-impedance during cutting tasks from human demonstrations, so as to ease soft-tissue cutting by robots. We model the dynamic adjustment of the human arm during interactions with the tissue and transfer these adaptive capabilities to the robot, by learning both the motion and change of impedance. To improve performance during task execution, our variable-impedance skill-transfer framework combines the learned model with an interactive-operation and feedback controller. To offer the flexibility of modifying the trajectory at run time, we use a control law based on dynamical systems. We couple this control law with virtual dynamics that describes the cutting dynamics. This ensures that the robot can control the interaction force and can plan the trajectory. The approach is validated in a real robot cutting-experiment of cutting different hardness tissues. Results show that our learning-based feedback controller, with the assistance from interactive-operation models, can effectively improve the task’s success rate, cutting length, cutting depth, and other indicators, as compared to using a fixed and variable-impedance gain controller.

2021

Controlling swimming and crawling in a fish robot using a central pattern generator

Auke Ijspeert, Alessandro Crespi, Daisy Lachat, Ariane Pasquier

Online trajectory generation for robots with multiple degrees of freedom is still a difficult and unsolved problem, in particular for non-steady state locomotion, that is, when the robot has to move in a complex environment with continuous variations of the speed, direction, and type of locomotor behavior. In this article we address the problem of controlling the non-steady state swimming and crawling of a novel fish robot. For this, we have designed a control architecture based on a central pattern generator (CPG) implemented as a system of coupled nonlinear oscillators. The CPG, like its biological counterpart, can produce coordinated patterns of rhythmic activity while being modulated by simple control parameters. To test our controller, we designed BoxyBot, a simple fish robot with three actuated fins capable of swimming in water and crawling on firm ground. Using the CPG model, the robot is capable of performing and switching between a variety of different locomotor behaviors such as swimming forwards, swimming backwards, turning, rolling, moving upwards/downwards, and crawling. These behaviors are triggered and modulated by sensory input provided by light, water, and touch sensors. Results are presented demonstrating the agility of the robot and interesting properties of a CPG-based control approach such as stability of the rhythmic patterns due to limit cycle behavior, and the production of smooth trajectories despite abrupt changes of control parameters. The robot is currently used in a temporary 20-month long exhibition at the EPFL. We present the hardware setup that was designed for the exhibition, and the type of interactions with the control system that allow visitors to influence the behavior of the robot. The exhibition is useful to test the robustness of the robot for long term use, and to demonstrate the suitability of the CPG-based approach for interactive control with a human in the loop. This article is an extended version of an article presented at BioRob2006 the first IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics.

2008

Controlling swimming and crawling in a fish robot using a central pattern generator

Auke Ijspeert, Alessandro Crespi, Daisy Lachat, Ariane Pasquier

2008