Multi-Resolution Hierarchical Motion Planner for Multi-Robot Systems on Spatiotemporal Cellular Automata

2014 ◽  
pp. 149-173
Author(s):  
Fabio M. Marchese
Keyword(s):  
Cellular Automata ◽  
Robot Systems ◽  
Multi Robot

scholarly journals Cellular Automata over Hexagonal and Triangular Tessellations for Path Planning

2019 ◽  
Vol 8 (4) ◽  
pp. 12395-12398
Keyword(s):  
Cellular Automata ◽  
Path Planning ◽  
Cellular Automaton ◽  
Robot Systems ◽  
Common Goals ◽  
Multi Robot

Exploring unknown terrains demand for the sophisticated algorithms for path planning in case of multi-robot systems. Robots searching for common goals are complicated as they need to avoid collisions. We need to provide paths for all robots which should be collision free and should take less amount of time. Usually these algorithms use square tessellations in this type of investigations, which leads to the lack of variation and enlargement of neighborhood. In this paper we present the construction of a cellular automaton over triangular and hexagonal tessellations and show the complexity for the same.

scholarly journals Resilient Task Allocation in Heterogeneous Multi-Robot Systems

2021 ◽  
Vol 6 (2) ◽  
pp. 1327-1334
Author(s):  
Siddharth Mayya ◽  
Diego S. D'antonio ◽  
David Saldana ◽  
Vijay Kumar
Keyword(s):  
Task Allocation ◽  
Robot Systems ◽  
Multi Robot

scholarly journals Exploring Robot Connectivity and Collaborative Sensing in a High-School Enrichment Program

Robotics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 13
Author(s):  
Igor M. Verner ◽  
Dan Cuperman ◽  
Michael Reitman
Keyword(s):  
High School ◽  
Positive Contribution ◽  
Smart Transportation ◽  
Sensory Data ◽  
Robot Systems ◽  
Enrichment Program ◽  
Collaborative Sensing ◽  
Robot Tasks ◽  
Value Of Learning ◽  
Multi Robot

Education is facing challenges to keep pace with the widespread introduction of robots and digital technologies in industry and everyday life. These challenges necessitate new approaches to impart students at all levels of education with the knowledge of smart connected robot systems. This paper presents the high-school enrichment program Intelligent Robotics and Smart Transportation, which implements an approach to teaching the concepts and skills of robot connectivity, collaborative sensing, and artificial intelligence, through practice with multi-robot systems. The students used a simple control language to program Bioloid wheeled robots and utilized Phyton and Robot Operating System (ROS) to program Tello drones and TurtleBots in a Linux environment. In their projects, the students implemented multi-robot tasks in which the robots exchanged sensory data via the internet. Our educational study evaluated the contribution of the program to students’ learning of connectivity and collaborative sensing of robot systems and their interest in modern robotics. The students’ responses indicated that the program had a high positive contribution to their knowledge and skills and fostered their interest in the learned subjects. The study revealed the value of learning of internet of things and collaborative sensing for enhancing this contribution.

scholarly journals Decentralized Task and Path Planning for Multi-Robot Systems

2021 ◽  
Vol 6 (3) ◽  
pp. 4337-4344
Author(s):  
Yuxiao Chen ◽  
Ugo Rosolia ◽  
Aaron D. Ames
Keyword(s):  
Path Planning ◽  
Robot Systems ◽  
Multi Robot

scholarly journals Robustness of Multi-Robot Systems Controlling the Size of the Connected Component After Robot Failure

2020 ◽  
Vol 53 (2) ◽  
pp. 3137-3143
Author(s):  
Toru Murayama ◽  
Lorenzo Sabattini
Keyword(s):  
Connected Component ◽  
Robot Systems ◽  
Multi Robot

scholarly journals Research Progress on Synergistic Technologies of Agricultural Multi-Robots

2021 ◽  
Vol 11 (4) ◽  
pp. 1448
Author(s):  
Wenju Mao ◽  
Zhijie Liu ◽  
Heng Liu ◽  
Fuzeng Yang ◽  
Meirong Wang
Keyword(s):  
Path Planning ◽  
Formation Control ◽  
Research Progress ◽  
Hybrid Architecture ◽  
Labor Costs ◽  
Robot System ◽  
System Architectures ◽  
Research Results ◽  
Robot Systems ◽  
Multi Robot

Multi-robots have shown good application prospects in agricultural production. Studying the synergistic technologies of agricultural multi-robots can not only improve the efficiency of the overall robot system and meet the needs of precision farming but also solve the problems of decreasing effective labor supply and increasing labor costs in agriculture. Therefore, starting from the point of view of an agricultural multiple robot system architectures, this paper reviews the representative research results of five synergistic technologies of agricultural multi-robots in recent years, namely, environment perception, task allocation, path planning, formation control, and communication, and summarizes the technological progress and development characteristics of these five technologies. Finally, because of these development characteristics, it is shown that the trends and research focus for agricultural multi-robots are to optimize the existing technologies and apply them to a variety of agricultural multi-robots, such as building a hybrid architecture of multi-robot systems, SLAM (simultaneous localization and mapping), cooperation learning of robots, hybrid path planning and formation reconstruction. While synergistic technologies of agricultural multi-robots are extremely challenging in production, in combination with previous research results for real agricultural multi-robots and social development demand, we conclude that it is realistic to expect automated multi-robot systems in the future.

scholarly journals Modelling and verification of reconfigurable multi-agent systems

2021 ◽  
Vol 35 (2) ◽  
Author(s):  
Yehia Abd Alrahman ◽  
Nir Piterman
Keyword(s):  
Model Checking ◽  
Communication Protocols ◽  
Local State ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Robot Systems ◽  
Message Exchange ◽  
Multi Agent ◽  
Exchange Data ◽  
Multi Robot

AbstractWe propose a formalism to model and reason about reconfigurable multi-agent systems. In our formalism, agents interact and communicate in different modes so that they can pursue joint tasks; agents may dynamically synchronize, exchange data, adapt their behaviour, and reconfigure their communication interfaces. Inspired by existing multi-robot systems, we represent a system as a set of agents (each with local state), executing independently and only influence each other by means of message exchange. Agents are able to sense their local states and partially their surroundings. We extend ltl to be able to reason explicitly about the intentions of agents in the interaction and their communication protocols. We also study the complexity of satisfiability and model-checking of this extension.

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