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mROBerTO 2.0 – An Autonomous Millirobot With Enhanced Locomotion for Swarm Robotics
- Source :
- IEEE Robotics and Automation Letters. 5:962-969
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- Numerous millirobots were developed in the past decade for autonomous swarm systems that aim to utilize large numbers of these units in space-constrained environments. However, the size limitation of these robots has often resulted in their reduced computational, sensing, and locomotion capabilities. mROBerTO (milli-ROBot-TOronto) was developed in response to such limitations. Despite its enhanced features, the reliable and repeatable locomotion of mROBerTO has still been of some concern due to lack of effective closed-loop motion control – as is the case with all other similar millirobots. In this letter, we present the next version of mROBerTO with a new locomotion mechanism that utilizes stepper motors, capable of micro-stepping down to 1/32 of a full step, to yield a millirobot with maneuvering capabilities superior to current similar-sized robots. mROBerTO 2.0 is novel in that it utilizes these stepper motors without relying on a separate processor for controlling them. This letter also presents a complementary new algorithm for efficiently converting desired trajectories into robot-motion commands. The proposed algorithm was developed to allow millirobots to execute complex trajectories reliably in an open-loop manner.
- Subjects :
- 0209 industrial biotechnology
Control and Optimization
Computer science
Mechanical Engineering
Biomedical Engineering
Swarm robotics
Swarm behaviour
Control engineering
02 engineering and technology
Motion control
Computer Science Applications
Human-Computer Interaction
020901 industrial engineering & automation
Artificial Intelligence
Control and Systems Engineering
0202 electrical engineering, electronic engineering, information engineering
Robot
020201 artificial intelligence & image processing
Computer Vision and Pattern Recognition
Subjects
Details
- ISSN :
- 23773774
- Volume :
- 5
- Database :
- OpenAIRE
- Journal :
- IEEE Robotics and Automation Letters
- Accession number :
- edsair.doi...........ac3b681633f3a1a6f9f09dddcac3ed40