Search results for "Robot"

Industrial Robot Collision Handling in Harsh Environments

2014

Doktorgradsavhandling i mekatronikk, Universitetet i Agder, 2014 The focus in this thesis is on robot collision handling systems, mainly collision detection and collision avoidance for industrial robots operating in harsh environments (e.g. potentially explosive atmospheres found in the oil and gas sector). Collision detection should prevent the robot from colliding and therefore avoid a potential accident. Collision avoidance builds on the concept of collision detection and aims at enabling the robot to find a collision free path circumventing the obstacle and leading to the goal position. The work has been done in collaboration with ABB Process Automation Division with focus on applicatio…

Self in NARS, an AGI System

2018

This article describes and discusses the self-related mechanisms of a general-purpose intelligent system, NARS. This system is designed to be adaptive and to work with insufficient knowledge and resources. The system’s various cognitive functions are uniformly carried out by a central reasoning-learning process following a “non-axiomatic” logic. This logic captures the regularities of human empirical reasoning, where all beliefs are revisable according to evidence, and the meaning of concepts are grounded in the system’s experience. NARS perceives its internal environment basically in the same way as how it perceives its external environment although the sensors involved are completely diff…

2020

In this paper a comprehensive system-level computational model of oculomotor pathways is presented. This model shows the necessity of embedding internal models of muscles biomechanics in the cerebellar Vermis to realize fast saccadic eye movements based on predicting the changes in muscles lengths. First, the eye biomechanics are described by nonlinear equations during “slow” and “fast” movements. Afterward, by analyzing these equations, a computational model, is deduced. Furthermore, each part of this model is interpreted as a possible function of an element in the oculomotor pathways based on physiological and anatomical pieces of evidence. In this model, two internal feedback loops compe…

Visual learning in Drosophila: Application on a roving robot and comparisons

2011

Visual learning is an important aspect of fly life. Flies are able to extract visual cues from objects, like colors, vertical and horizontal distributedness, and others, that can be used for learning to associate a meaning to specific features (i.e. a reward or a punishment). Interesting biological experiments show trained stationary flying flies avoiding flying towards specific visual objects, appearing on the surrounding environment. Wild-type flies effectively learn to avoid those objects but this is not the case for the learning mutant rutabaga defective in the cyclic AMP dependent pathway for plasticity. A bio-inspired architecture has been proposed to model the fly behavior and experi…

Mesoscale eddies, surface circulation and the scale of habitat selection by immature loggerhead sea turtles

2007

17 pages, 8 figures, 6 tables

Palvelurobotiikka

2018

Des robots et des hommes

2006

My Extended Body - From Cyborgs to Robots to Cyborgs

2019

Toward Self-Aware Robots

2018

Despite major progress in Robotics and AI, robots are still basically “zombies” repeatedly achieving actions and tasks without understanding what they are doing. Deep-Learning AI programs classify tremendous amounts of data without grasping the meaning of their inputs or outputs. We still lack a genuine theory of the underlying principles and methods that would enable robots to understand their environment, to be cognizant of what they do, to take appropriate and timely initiatives, to learn from their own experience and to show that they know that they have learned and how. The rationale of this paper is that the understanding of its environment by an agent (the agent itself and its effect…

Experiments in Artificial Theory of Mind: From Safety to Story-Telling

2018

Theory of mind is the term given by philosophers and psychologists for the ability to form a predictive model of self and others. In this paper we focus on synthetic models of theory of mind. We contend firstly that such models—especially when tested experimentally—can provide useful insights into cognition, and secondly that artificial theory of mind can provide intelligent robots with powerful new capabilities, in particular social intelligence for human-robot interaction. This paper advances the hypothesis that simulation-based internal models offer a powerful and realisable, theory-driven basis for artificial theory of mind. Proposed as a computational model of the simulation theory of …