A Neural Approach for the Control of Piezoelectric Micromanipulation Robots

Micromanipulation has become an issue of primary importance in industry and biomedicine, since human manual capabilities are restricted to certain tolerances. The manipulation of biological cells or the assembly of a complete microsystem composed of different microcomponents are examples of the application of piezoelectric-driven microrobots. An automated microrobot-based micromanipulation desktop-station is developed by an interdisciplinary group at the University of Karlsruhe. The process of assembly takes place in the field of view of a light optical microscope. This paper focuses on motion control problems of the microrobots. The ability of an intelligent microsystem to adapt itself to the process requirements is of great importance, especially for assembly robots. The microrobots must be able to operate in a partially defined environment and to ensure reasonable behaviour in unpredicted situations. A neural control concept based on a reference model approach is proposed as a solution. It is shown, that the neural controller is able to learn the desired behaviour. It considerably outperforms an analytically designed linear controller. This is demonstrated both in simulation and in the real environment.     

Control system for motion control of a piezoelectric micromanipulation robot

Abstraet-Micromanipulation by microrobots has become an issue of primary importance in industry and biomedicine, since human manual capabilities are restricted to certain tolerances. The manipulation of biological cells or the assembly of a microsystem composed of several microcomponents are good examples. An automated microrobot-based micromanipulation desktop station has been developed at the University of Karlsruhe. The process of assembly takes place in the field of view of a light optical microscope. This paper focuses on motion control problems of the piezo-driven microrobots employed by the station. The ability to adapt itself to the process requirements is of great importance for micromanipulation robots. They must be able to operate in a partially defined environment and to ensure reasonable behavior in unpredicted situations. A neural control concept based on a reference model is proposed as a solution. It is shown that the neural controller is able to learn the desired behavior. It considerably outperforms an analytically designed linear controller in the real environment.     

A formal framework for design and verification of robotic agents

Intelligent robots are autonomous and are used in environments where human interaction is hazardous or impossible. Verification of software for intelligent robots is mandatory because in situations where intelligent robots are employed online, error recovery is almost impossible. In this paper, we provide a formal framework for offline verification of software used in robotic applications. The specification enables one to design a robotic agent which represents a class of real-life robots. Forward and inverse kinematic operations of the robotic agent are specified using the specification for rigid solids and their primitive operations. An object-oriented design of the robotic agent derived from the specifications is given. We use the specification technique VDM for our purpose.This work was partially supported by FCAR, Quebec and NSERC, Canada.     

Collective energy homeostasis in a large-scale microrobotic swarm

This paper introduces an approach that allows swarm robots to maintain their individual and collective energetic homeostasis. The on-board recharging electronics and intelligent docking stations enable the robots to perform autonomous recharging from low energy states. The procedure of collective decision-making increases collective efficiency by preventing bottlenecks at docking stations and the energetic death of low-energy robots. These hardware and behavioral mechanisms are implemented in a swarm of real microrobots, and several analogies to self-regulating biological strategies are found.     

A Study on Development of a Hybrid Aerial/Terrestrial Robot System for Avoiding Ground Obstacles by Flight

To date, many studies related to robots have been performed around the world. Many of these studies have assumed operation at locations where entry is difficult, such as disaster sites, and have focused on various terrestrial robots, such as snake-like, humanoid, spider-type, and wheeled units. Another area of active research in recent years has been aerial robots with small helicopters for operation indoors and outdoors. However, less research has been performed on robots that operate both on the ground and in the air. Accordingly, in this paper, we propose a hybrid aerial/terrestrial robot system. The proposed robot system was developed by equipping a quadcopter with a mechanism for ground movement. It does not use power dedicated to ground movement, and instead uses the flight mechanism of the quadcopter to achieve ground movement as well. Furthermore, we addressed the issue of obstacle avoidance as part of studies on autonomous control. Thus, we found that autonomous control of ground movement and flight was possible for the hybrid aerial/terrestrial robot system, as was autonomous obstacle avoidance by flight when an obstacle appeared during ground movement.      

CAMPOUT: a control architecture for tightly coupled coordination of multirobot systems for planetary surface exploration

Exploration of high risk terrain areas such as cliff faces and site construction operations by autonomous robotic systems on Mars requires a control architecture that is able to autonomously adapt to uncertainties in knowledge of the environment. We report on the development of a software/hardware framework for cooperating multiple robots performing such tightly coordinated tasks. This work builds on our earlier research into autonomous planetary rovers and robot arms. Here, we seek to closely coordinate the mobility and manipulation of multiple robots to perform examples of a cliff traverse for science data acquisition, and site construction operations including grasping, hoisting, and transport of extended objects such as large array sensors over natural, unpredictable terrain. In support of this work we have developed an enabling distributed control architecture called control architecture for multirobot planetary outposts (CAMPOUT) wherein integrated multirobot mobility and control mechanisms are derived as group compositions and coordination of more basic behaviors under a task-level multiagent planner. CAMPOUT includes the necessary group behaviors and communication mechanisms for coordinated/cooperative control of heterogeneous robotic platforms. In this paper, we describe CAMPOUT, and its application to ongoing physical experiments with multirobot systems at the Jet Propulsion Laboratory in Pasadena, CA, for exploration of cliff faces and deployment of extended payloads.     

Hardware-in-the-Loop Verification for Mobile Manipulating Unmanned Aerial Vehicles

A hardware-in-the-loop test rig is presented to bridge the gap between basic aerial manipulation research and the ability of flying robots to perform tasks such as bridge repair, agriculture care, container inspection and other applications requiring interaction with the environment. Unmanned aerial vehicles have speed and mobility advantages over ground vehicles and can operate in 3-dimensional workspaces. In particular, the usefulness of these capabilities is highlighted in areas where ground robots cannot reach or terrains they are unable to navigate. However, most UAVs operating in near-earth or indoor environments still do not have the payload capabilities to support multi-degree of freedom manipulators. We present a rotorcraft emulation environment using a 7 degree of freedom manipulator. Since UAVs require significant setup time and to avoid potential crashes, our test and evaluation environment provides repeatable experiments and captures reactionary forces experienced during ground interaction. Recent experiments in insertion tests are presented. The lessons learned from these experiments will be ported onto an actual air vehicle with manipulator.     

Moving robot’s mind of autonomous decentralized FMS and mind change control

This article describes the control of moving robots in an autonomous decentralized flexible manufacturing system (FMS) by changing the mind of the moving robot. In an autonomous decentralized flexible manufacturing system where a lot of moving robots operate, there are problems of path interference. There is an existing method which we have developed called AAA, and this is used to evade these interference problems. However, using this method, it is very difficult to grasp entirely the innumerable path interference situations that really occur. Therefore, to evade these unexpected situations flexibly, we propose a mind model, which is the complicated expression of combinations of three elements: stimulation vector, unit, and load. Even if a familiar situation happens, moving robots can make different actions when their mind is changed.