The chapter also discusses a new method of using robots to interact with humans (natural interaction) to provide assistance services. Using depth sensors, the robots are able to detect the human operator and to avoid collisions. Collision avoidance is implemented using a depth sensor, which monitors the activity outside and inside the multi-robot system workspace, using skeleton tracking, which allows the robot to detect collisions and stop the motion at the right time.
TopIntroduction
Recent research activities have been directed toward designing multiple robot systems engaged in collective tasks. Such systems are of interest for several reasons:
- •
Service tasks may be inherently too complex for a single robot to be accomplished (or impossible to be accomplished), or performance benefits can be gained using multiple robots in a global task-oriented behaviour;
- •
Building and using several simple robots can be easier, cheaper, more flexible and more fault tolerant than having a single powerful robot for each separate service task.
The chapter presents a new method of controlling multiple industrial robots in cooperative tasks without using force sensors. Instead, a motion planner is used which computes the trajectory of the handled object, and then decomposes this trajectory into multiple trajectories associated to each robot involved in the task. The trajectory is then executed using small motion increments and I/O synchronization.
In hardware and software reconfigurable manufacturing environments the robots can be used in complex tasks, such as: cooperation with machine tools for part loading / unloading and processing, cooperation with other robot for heavy part handling, precision assembly and high-speed simultaneous part processing and multiple, high-speed vision-based access to moving parts on conveyor belts; these part handling services require multi-robot control. Therefore, in most implementations emergency stops are connected separately to each robot and also for the entire system. Light barriers surround the working area offering protection to the human operator by stopping the robot task if the barrier is crossed. In many situations the operator must enter in the robot workspace for maintenance tasks and the robots will be stopped even if no intervention is executed on them, in order to prevent a possible human injury.
The chapter proposes a solution to solve security problems without stopping the robot if the operator enters its workspace but does not interfere with it, based on a depth sensor, which detects human activities inside the work cell. The robot motion speed will be decreased proportionally with the relative distance between the operator and the robot. The sensor is also used to send different simple commands to the robot by identifying the operator posture or full body gestures.
The chapter reports experimental results obtained in the Laboratory of Robotics and Artificial Intelligence of the Dept. of Automation and Applied Informatics within the University Politehnica of Bucharest, and suggests some future research directions for dual robot cooperation in manufacturing services, and robot-human natural interaction in assisting tasks.
TopBackground
Studies concerning multiple-robot systems naturally extend the research on single-robot systems, but represent also a discipline itself: multiple-robot systems can accomplish tasks that no single robot can accomplish, since ultimately a single robot, no matter how capable, is spatially limited (Caccavale & Uchiyama, 2008).
Modelling and controlling multiple robot manipulators handling constrained an object require more sophisticated techniques as compared with a single robot working alone. Since the theory employed for cooperative robots is independent of their size, one can think of them as mechanical hands.
Robot hands (as well as cooperative robots), find many areas of application nowadays. Many benefits can be obtained by using them in industrial manufacturing. A typical example is flexible assembly, where the robots assemble parts into products (Guidino-Lau & Arteaga, 2006).
Robots working in a cooperative manner can also be used in material handling, e.g., transporting objects beyond the load carrying capacity of a single robot. Furthermore, their employment allows improving the quality of tasks in the manufacturing industry requiring high precision.
From another point of view, cooperative robots are indispensable for high-precision skilful grasping and dexterous manipulation of objects. However, the literature about experimental results on the modelling, simulation and control of systems of multiple manipulators holding a common object is rather sparse.