• Corpus ID: 218486850

"Can you do this?" Self-Assessment Dialogues with Autonomous Robots Before, During, and After a Mission

  title={"Can you do this?" Self-Assessment Dialogues with Autonomous Robots Before, During, and After a Mission},
  author={Tyler M. Frasca and Evan A. Krause and Ravenna Thielstrom and matthias. scheutz},
Autonomous robots with sophisticated capabilities can make it difficult for human instructors to assess its capabilities and proficiencies. Therefore, it is important future robots have the ability to: introspect on their capabilities and assess their task performance. Introspection allows the robot to determine what it can accomplish and self-assessment allows the robot estimate the likelihood it will accomplish at given task. We introduce a general framework for introspection and self… 
1 Citations

Tables and Topics from this paper

Why and How Robots Should Say ‘No’
Language-enabled robots with moral reasoning capabilities will inevitably face situations in which they have to respond to human commands that might violate normative principles and could cause harm


How can a robot evaluate its own behavior? A neural model for self-assessment
This work presents two different sensorimotor strategies the authors' robot can use to navigate and presents a neural architecture that may be able to evaluate both navigation strategies, based on an online novelty detection algorithm using a neural predictor.
Analogical Generalization of Actions from Single Exemplars in a Robotic Architecture
This paper shows how a robot can generate variations of a given scenario and then use the results of those new scenarios run in a physics simulator to generate generalized action scripts using analogical mappings.
Crossing Boundaries: Multi-Level Introspection in a Complex Robotic Architecture for Automatic Performance Improvements
This work introduces a novel multi-level introspection framework that can be used to automatically adjust architectural configurations based on the introspection results at the agent, infrastructure and component level and demonstrates the utility of such adjustments in a concrete implementation on a robot.
DIARC: A Testbed for Natural Human-Robot Interaction
The architecture and and its implementation in ADE is described, paying particular attention to its interaction capabilities and features that allow robust operation.
Novel Mechanisms for Natural Human-Robot Interactions in the DIARC Architecture
Natural human-like human-robot interactions require many functional capabilities from a robot that have to be reflected in architectural components in the robotic control architecture. In particular,
A game theoretic queueing approach to self-assessment in human-robot interaction systems
A queueing model that addresses robot self-assessment in human-robot-interaction systems based on a game theoretic queueing approach is presented, and the impact of task heterogeneity in the optimal service decision-making and system performance is analyzed.
Knowing your limits - self-evaluation and prediction in object recognition
Probabilistic measures for observed detection success, predicted detection success and the completeness of learned models are presented, where learning is incremental and online.
An Overview of the Distributed Integrated Affect and Reflection Cognitive DIARC Architecture
  • In Cognitive Architectures. Intelligent Systems, Control and Automation: Science and Engineering book series,
  • 2019