Performance of a distributed robotic system using shared communications channels

Abstract

Abstract-We have designed and built a set of miniature robots, called Scouts, and have developed a distributed software system to control them. This paper addresses the fundamental choices we made in the design of the control software, describes experimental results in a surveillance task, and analyzes the factors that affect robot performance.Space and power limitations on the Scouts severely restrict the computational power of their on-board computers, requiring a proxy-processing scheme in which the robots depend on remote computers for their computing needs. While this allows the robots to be autonomous, the fact that robots' behaviors are executed remotely introduces an additional complication -sensor data and motion commands have to be exchanged using wireless communications channels. Communications channels cannot always be shared, thus requiring the robots to obtain exclusive access to them.We present experimental results on a surveillance task in which multiple robots patrol an area and watch for motion. We discuss how the limited communications bandwidth affects robot performance in accomplishing the task and analyze how performance depends on the number of robots that share the bandwidth.

Robot-Assisted Surveillance in Large Environments

“…Again, the robots need enough computational power to manage a differential GPS receiver, an IMU, video cameras and a color-tracking vision system. In [5] a multirobot surveillance system is presented, describing how a group of miniature robots (called Scouts) accomplishes simple surveillance tasks using an on-board video camera. Because of limitations on the space and power supply available on-board, Scouts rely on remote computers to manage all the resources, to compute decision processes, and finally to provide them with control commands.…”

“…With the sole exception of [5], autonomous self-localization and navigation capabilities are fundamental prerequisites in all the robot-based surveillance systems. Starting from a minimal configuration including an IMU and a carrier phase differential GPS receiver [6 − 9], a common approach to self-localization is to equip the mobile platform with redundant sensory, thus requiring high computational power and complex data filtering.…”

Multi-Robot Systems and Distributed Intelligence: The ETHNOS Approach to Heterogeneity

“…In this perspective, Multi Robot systems are an obvious choice for all those applications which implicitly take benefit of redundancy; i.e., applications in which, even in absence of a coordination strategy, having more robots working in parallel improves the system's fault tolerance, reduces the time required to execute tasks, guarantees a higher service availability and a quicker response to user requests. There are many cases for which this holds: autonomous cleaning (Jung & Zelinski, 2000;Kurazume et al, 2000); tour guiding in museums, art-galleries, or exhibitions (Siegwart et al, 2003); surveillance and patrolling (Rybski et al, 2002;Vidal et al, 2002), rescue in large scale disaster such as fires, floods, earthquakes (Bahadori et al, 2005); landmine detection (Acar et al, 2003); autonomous exploration and mapping, possibly with the additional constraint of retrieving samples or objects of interests (Rekleitis et al, 2000;Burgard et al, 2005). All the previous applications share some common characteristics: they require the execution of a set of loosely coupled tasks more or less comparable to "coverage", i.e., the problem of visiting the largest number of locations in a given area (Fontan & Matarić, 1996;Choset, 2001), and "foraging", i.e., the problem of finding objects or persons of interest ("food", in the metaphor) and returning them to a specified location (Arkin, 1992;Drgoul & Ferber, 1993).…”

Communication Strategies in Multi-robot Search and Retrieval: Experiences with MinDART

“…While collaboration may be essential for some tasks, we are interested in studying tasks that can be done by a single robot, but where using multiple robots can potentially increase performance by decreasing the time to complete the task and/or by increasing the reliability. Sample tasks include placing a sensor network [16], cleaning up trash [12], pushing boxes [9], or detecting odors [5].…”