Efficient Multi-Robot Coverage of a Known Environment

This paper addresses the complete area coverage problem of a known environment by multiple-robots. Complete area coverage is the problem of moving an end-effector over all available space while avoiding existing obstacles. In such tasks, using multiple robots can increase the efficiency of the area coverage in terms of minimizing the operational time and increase the robustness in the face of robot attrition. Unfortunately, the problem of finding an optimal solution for such an area coverage problem with multiple robots is known to be NP-complete. In this paper we present two approximation heuristics for solving the multi-robot coverage problem. The first solution presented is a direct extension of an efficient single robot area coverage algorithm, based on an exact cellular decomposition. The second algorithm is a greedy approach that divides the area into equal regions and applies an efficient single-robot coverage algorithm to each region. We present experimental results for two algorithms. Results indicate that our approaches provide good coverage distribution between robots and minimize the workload per robot, meanwhile ensuring complete coverage of the area.Comment: In proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 201

Planning for Decentralized Control of Multiple Robots Under Uncertainty

We describe a probabilistic framework for synthesizing control policies for general multi-robot systems, given environment and sensor models and a cost function. Decentralized, partially observable Markov decision processes (Dec-POMDPs) are a general model of decision processes where a team of agents must cooperate to optimize some objective (specified by a shared reward or cost function) in the presence of uncertainty, but where communication limitations mean that the agents cannot share their state, so execution must proceed in a decentralized fashion. While Dec-POMDPs are typically intractable to solve for real-world problems, recent research on the use of macro-actions in Dec-POMDPs has significantly increased the size of problem that can be practically solved as a Dec-POMDP. We describe this general model, and show how, in contrast to most existing methods that are specialized to a particular problem class, it can synthesize control policies that use whatever opportunities for coordination are present in the problem, while balancing off uncertainty in outcomes, sensor information, and information about other agents. We use three variations on a warehouse task to show that a single planner of this type can generate cooperative behavior using task allocation, direct communication, and signaling, as appropriate

Corporation robots

Nowadays, various robots are built to perform multiple tasks. Multiple robots working together to perform a single task becomes important. One of the key elements for multiple robots to work together is the robot need to able to follow another robot. This project is mainly concerned on the design and construction of the robots that can follow line. In this project, focuses on building line following robots leader and slave. Both of these robots will follow the line and carry load. A Single robot has a limitation on handle load capacity such as cannot handle heavy load and cannot handle long size load. To overcome this limitation an easier way is to have a groups of mobile robots working together to accomplish an aim that no single robot can do alon

Teamwork in controlling multiple robots

Simultaneously controlling increasing numbers of robots requires multiple operators working together as a team. Helping operators allocate attention among different robots and determining how to construct the human-robot team to promote performance and reduce workload are critical questions that must be answered in these settings. To this end, we investigated the effect of team structure and search guidance on operators' performance, subjective workload, work processes and communication. To investigate team structure in an urban search and rescue setting, we compared a pooled condition, in which team members shared control of 24 robots, with a sector condition, in which each team member control half of all the robots. For search guidance, a notification was given when the operator spent too much time on one robot and either suggested or forced the operator to change to another robot. A total of 48 participants completed the experiment with two persons forming one team. The results demonstrate that automated search guidance neither increased nor decreased performance. However, suggested search guidance decreased average task completion time in Sector teams. Search guidance also influenced operators' teleoperation behaviors. For team structure, pooled teams experienced lower subjective workload than sector teams. Pooled teams communicated more than sector teams, but sector teams teleoperated more than pool teams.United States. Office of Naval ResearchUnited States. Air Force Office of Scientific Researc

Data Exchange among Multiple Robots

Communication subsystem in robotics is one of the important parts of a system, often being used before going to larger communication system. Communication subsystem is essential for one device to communicate with other devices in terms of movement and also location. In this project, data exchange between multiple robots need to be accurate, fast and yet reliable in term of movement and direction. Therefore, by designing a hardware-software, communication between three robots is being established pertaining their movement and direction. Communications between master and slave has been established where the slaves are able to receive the data pertaining to the master