Vanderbilt University

DARPA Mobile Autonomous Robot Software (MARS) Program Overview

 

 


 

Mobile Robot Research

Humanoid Robot Research

Knowledge Sharing Group

Robot Convoy Group

ISAC Group

SMC Group

  • Planning / Control Framework
  • Navigation Behaviors / Skill
  • Commander Agent and Self Agent
  • Human - Humanoid Interaction
  • Supporting technologies: SSE, SES, DBAM, SAN
  • Learning
  • Sensory Motor Control
 

Intelligent Robotics Lab

Cognitive Robotics Lab

 

Project Goal


Develop software control system for autonomous mobile robots that:

  • accept mission-level commands

  • learn from experience to use / acquire behaviors

  • can be trained with intuitive interface

  • share learned knowledge with other robots

 

Project Approach


 


During the first year, a multi-agent based Human-Robot Interface (HRI) approached was designed and the following key components were developed: the Self Agent, a compound agent responsible for monitoring the status of the robot itself and communication with the human commander and other robots; the Sensory EgoSphere (SES), a short-term memory data structure for dynamically storing sensor data; the Database Associative Memory (DBAM), a long-term memory in which records are linked through a spreading activation network (SAN).

During the second year, various behavior agents were developed for mobile robots including the ATRV-Jr, Pioneer-2-AT, HelpMate and Trilobot robots.  A user-centric GUI for the ATRV-Jr and the HelpMate was developed. A mission planner was developed and will be integrated into the GUI. We design and implemented Sensory EgoSphere (SES)- and Landmark EgoSphere (LES)-based navigation and knowledge sharing using the ATRV-Jr and Pioneer2 robots. Robot learning was developed and tested on the ATRV-Jr using reinforcement learning algorithm.