Intention from Motion
نویسندگان
چکیده
Intention from Motion Christopher Crick 2009 I present a system which observes humans participating in various playground games and infers their goals and intentions through detecting and analyzing their spatiotemporal activity in relation to one another, and then builds a coherent narrative out of the succession of these intentional states. I show that these narratives capture a great deal of essential information about the observed social roles, types of activity and game rules by demonstrating the system's ability to correctly recognize and group together different runs of the same game, while differentiating them from other games. The system can build a coherent account of the actions it witnesses similar to the stories humans tell. Furthermore, the system can use the narratives it constructs to learn and theorize about novel observations, allowing it to guess at the rules governing the games it watches. Thus a rich and layered trove of social, intentional and cultural information can be drawn out of extremely impoverished and low-context trajectory data. I then develop this process into a novel, sophisticated intention-based control system for a mobile robot. The system observes humans participating in various playground games, infers their goals and intentions through analyzing their spatiotemporal activity in relation to itself and each other, and then builds a coherent narrative out of the succession of these intentional states. Starting from zero information about the room or the rules of the games, it learns rich relationships between players, their goals and intentions, probing uncertain situations with its own behavior. The robot is able to watch people playing various playground games, learn the roles and rules that apply to specific games, and participate in the play. The narratives it constructs capture essential information about the observed social roles and types of activity. After watching play for a short while, the system participates appropriately in the games. I demonstrate how the system copes with scenarios such as chasing, follow-the-leader and tag.
منابع مشابه
Motion Intention Recognition for Wearable Power Assist System using Multi-Class SVM and Kinematic Model
This paper is aimed at describing a framework to implement Multi-Class Support Vector Machine (MCSVM)-based motion intention recognition. To this end, we primarily constructed a wearable exoskeleton robot of lower body which is employed as an experimentation platform to test the MCSVM-based motion intention recognition. Having disclosed prototype development and MCSVM, experimental results of m...
متن کاملMotion estimation for gait rehabilitation of hemiplegic patients using principal components analysis
In gait rehabilitation of hemiplegic patients by means of a robotic orthosis, a major challenge resides in cooperative control. The patient should not simply be moved, but rather be assisted in his motions. Ideally, the controller should thus detect the patient's intention and actuate his paretic limbs coordinately. Recently, good results have been achieved with impedance control, which gives t...
متن کاملExploration of neural correlates of movement intention based on characterisation of temporal dependencies in electroencephalography
Brain computer interfaces (BCIs) provide a direct communication channel by using brain signals, enabling patients with motor impairments to interact with external devices. Motion intention detection is useful for intuitive movement-based BCI as movement is the fundamental mode of interaction with the environment. The aim of this paper is to investigate the temporal dynamics of brain processes u...
متن کاملIntention-Net: Integrating Planning and Deep Learning for Goal-Directed Autonomous Navigation
How can a delivery robot navigate reliably to a destination in a new office building, with minimal prior information? To tackle this challenge, this paper introduces a two-level hierarchical approach, which integrates model-free deep learning and model-based path planning. At the low level, a neural-network motion controller, called the intention-net, is trained end-to-end to provide robust loc...
متن کاملIntention from Motion
In this paper, we propose Intention from Motion, a new paradigm for action prediction where, without using any contextual information, we can predict human intentions all originating from the same motor act, non specific of the following performed action. To this purpose, we have designed a new multimodal dataset consisting of a set of motion capture marker 3D data and 2D video sequences where,...
متن کاملIntention attribution in the pSTS 1 Running head: INTENTION ATTRIBUTION IN THE PSTS Attributing intentions to random motion engages the posterior superior temporal sulcus
The right posterior superior temporal sulcus (pSTS) is a neural region involved in assessing the goals and intentions underlying the motion of social agents. Recent research has identified visual cues, such as chasing, that trigger animacy detection and intention attribution. When readily available in a visual display, these cues reliably activate the pSTS. Here, using functional magnetic reson...
متن کامل