Fusion of ranging data from robot teams operating in confined areas

Abstract

We address the problem of fusing laser ranging data from multiple mobile robots that are surveying an area as part of a robot search and rescue or area surveillance mission. We are specifically interested in the case where members of the robot team are working in close proximity to each other. The advantage of this teamwork is that it greatly speeds up the surveying process; the area can be quickly covered even when the robots use a random motion exploration approach. However, the disadvantage of the close proximity is that it is possible, and even likely, that the laser ranging data from one robot include many depth readings caused by another robot. We refer to this as mutual interference. Using a team of two Pioneer 3-AT robots with tilted SICK LMS-200 laser sensors, we evaluate several techniques for fusing the laser ranging information so as to eliminate the mutual interference. There is an extensive literature on the mapping and localization aspect of this problem. Recent work on mapping has begun to address dynamic or transient objects. Our problem differs from the dynamic map problem in that we look at one kind of transient map feature, other robots, and we know that we wish to completely eliminate the feature. We present and evaluate three different approaches to the map fusion problem: a robot-centric approach, based on estimating team member locations; a map-centric approach, based on inspecting local regions of the map, and a combination of both approaches. We show results for these approaches for several experiments for a two robot team operating in a confined indoor environment .

Leveraging Area Bounds Information for Autonomous Multirobot Exploration

“…Robot interference with each other's sensor readings is another cause of error. No filtering was added to eliminate these mutually interfering sensor readings (e.g., as in [5]) and to record a robot as a permanent obstacle with appropriately high repulsive effect.…”

“…However they focus on feature-recognition and merging data from multiple robots. Lyons et al [5] discuss gridbased methods to combine maps so as to avoid transitory readings from other robots.…”

Leveraging area bounds information for autonomous decentralized multi-robot exploration

“…However they focus on feature-recognition and merging data from multiple robots. Lyons et al [26] discuss grid-based methods to combine maps so as to avoid transitory readings from other robots. In this paper, the occupancy grid contains information about obstacles sensed and information about exploration coverage.…”

Evaluation of parallel reduction strategies for fusion of sensory information from a robot team

“…We have used a simple modification of the common horizontal laser configuration to allow us to generate 3-D information as a robot moves: a single, tilted laser. The complementary nature of these two laser robots and their use in constructing a 3D model has been described in [3]. All the robots have onboard computers and are programmed using the Aria toolkit in C++.…”

“…In prior work, we have investigated how to quickly deploy a team of robots across a building [1] [2] as well as how to combine the sensory data from a team of robots working together so as to eliminate transient mutual views [3] [4]. The architecture used in these experiments is shown in Figure 1: As members of the robot team are dispersed through the building they all transmit their sensory data to a remote command center for registration, fusion and filtering.…”