Arrow Research search
Back to IROS

IROS 2013

Interactive environment exploration in clutter

Conference Paper Accepted Paper Artificial Intelligence · Robotics

Abstract

Robotic environment exploration in cluttered environments is a challenging problem. The number and variety of objects present not only make perception very difficult but also introduce many constraints for robot navigation and manipulation. In this paper, we investigate the idea of exploring a small, bounded environment (e. g. , the shelf of a home refrigerator) by prehensile and non-prehensile manipulation of the objects it contains. The presence of multiple objects results in partial and occluded views of the scene. This inherent uncertainty in the scene's state forces the robot to adopt an observe-plan-act strategy and interleave planning with execution. Objects occupying the space and potentially occluding other hidden objects are rearranged to reveal more of the unseen area. The environment is considered explored when the state (free or occupied) of every voxel in the volume is known. The presented algorithm can be easily adapted to real world problems like object search, taking inventory, and mapping. We evaluate our planner in simulation using various metrics like planning time, number of actions required, and length of planning horizon. We then present an implementation on the PR2 robot and use it for object search in clutter.

Authors

Keywords

  • Planning
  • Search problems
  • Clutter
  • Robot sensing systems
  • Robot kinematics
  • Cameras
  • Interactive Exploration
  • Exploration Of Environment
  • Number Of Objects
  • Real-world Problems
  • Robot Manipulator
  • Voxel Volume
  • Planning Time
  • Planning Horizon
  • Hidden Object
  • View Of The Scene
  • Cluttered Environments
  • Free Space
  • Sequence Of Actions
  • Adaptive Algorithm
  • Object Recognition
  • Point Cloud
  • Bounding Box
  • Information Gain
  • Kinds Of Activities
  • Detailed Algorithm
  • Objects In The Scene
  • Target Object
  • Object Placement
  • Object Counting
  • Real Robot
  • Action Execution
  • Object Motion
  • Longer Horizons
  • Exploration Algorithm
  • Object Size

Context

Venue
IEEE/RSJ International Conference on Intelligent Robots and Systems
Archive span
1988-2025
Indexed papers
26578
Paper id
930551173999943480