Abstract
In this paper we present a new approach to cooperative overhead object transportation with obstacle avoidance for multi-robot systems. This approach considers situations in which there are obstacles that only pose a risk to the robots involved in the transport and not necessarily to the group of robots with the load. Thus, we propose to separate the workspace into two layers in a way that the obstacles which only pose risk of collision to the robots can be transposed by a local planner. This new approach to the load transportation problem allows the system to find shorter paths or even find a solution in situations which would not be possible with the classic approach. Furthermore, the developed method has a configuration space independent of the number of robots and it is robust to environmental variation, not reducing its performance in more complex environments as in narrow passages or long corridors. The proposed approach was tested by simulation and the results are compared to the classic one.
Highlights
In recent years, there has been increasing research interest in load transport by multi-robot systems (MRSs), making it an emerging field [1]–[4]
The proposed approach is compared to the classical method, which is performed by replanning the path for the entire virtual structure when it finds an unknown obstacle
In this paper, a new way of approaching the problem of cargo transport by MRS with obstacle avoidance was presented, considering that there are two different classes of obstacles: those that can collide with the load and that are known a priori, and those that can only collide with one or more robots, unknown a priori, but which are visible by the sensors embedded in the robots
Summary
There has been increasing research interest in load transport by multi-robot systems (MRSs), making it an emerging field [1]–[4]. A cooperative team of robots can perform a transport task even if some robots fail. They can transport large and heavy objects in challenging environments [5]. Cooperative handling and transport of heavy payloads is required in a number of potential MRS applications [6], including construction, manufacturing, and automated warehouses [7]; disaster response and search and rescue mis-. Over the past 20 years, load transport by MRS has become a classic task to study cooperation in robot groups. The strategies used are traditionally divided into three most common types: pushing, caging and grasping [1]
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