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University of Nevada - Reno

Object Detection and Collaboration in Heterogeneous Multi-Robot Systems

Abstract

dc:description.abstract

With the development of novel technologies, robots are becoming more widely used in everyday applications. Compared with a single robot, Multi-Robot Systems (MRS) are more powerful and cost effective. This thesis will introduce a complete heterogeneous distributed MRS which contains an autonomous mobile robot (Pioneer 3-DX) and a stationary humanoid robot (Baxter), which are able to jointly perform a task that involves navigation and object manipulation. The contributions of this thesis are: 1) we developed an object detection system, locating the pose of objects with a depthcamera through OpenCV and the HSV color model; 2) we optimized a path planning and control system which would enable the Pioneer 3-DX to map its surrounding environment and navigate to target poses, as well as allow the Baxter to grasp, lift and drop the target objects using the MoveIt framework accurately and successfully; 3) we developed a distributed communication system so as to allow two different functional robots to communicate with each other through ROS 2. These contributions are validated with a heterogeneous robot team, including an autonomous mobile robot and a humanoid robot, completing tasks collaboratively.

Degree

thesis:*
Level thesis:degree_level
Master's Degree
Year dc:date.issued
2022

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Jiang, Song
Advisor dc:contributor.advisor
  • Nicolescu, Monica
Committee members dc:contributor.committeemember
  • Nicolescu, Mircea
  • Panorska, Anna

Subjects

dc:subject × 4

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/11714/8175
OAI identifier oai:identifier
oai:scholarwolf.unr.edu:11714/8175

Chain of custody

source
Harvested from
University of Nevada - Reno
Base URL
scholarwolf.unr.edu/server/oai/request
Last updated
2026-07-27
Source record
OAI-PMH GetRecord
citation

Jiang, Song. Object Detection and Collaboration in Heterogeneous Multi-Robot Systems. Master's Degree thesis, 2022. http://hdl.handle.net/11714/8175