Automated robotic grinding by low-powered manipulator

A new robotic grinding process has been developed for a low-powered robot system using a spring balancer as a suspension system. To manipulate a robot-arm in the vertical plane, a large actuator torque is required due to the tool weight and enormous gravity effect. But the actuators of the robot system always exhibit a limited torque capacity. This paper presents a cheap and available system for precise grinding tasks by a low-powered robot system using a suspension system. For grinding operations, to achieve position and force-tracking simultaneously, this paper presents an algorithm of the hybrid position/force-tracking scheme with respect to the dynamic behavior of a spring balancer. Material Removal Rate (MRR) is developed for materials SS400 and SUS304. Simulations and experiments have been carried out to demonstrate the feasibility of the proposed system.

DEVELOPMENT OF A HUMANOID ROBOT ARM FOR USE IN URBAN ENVIRONMENTS

The Bucknell Humanoid Robot Arm project was developed in order toprovide a lightweight robotic arm for the IHMC / Bucknell University bipedal robot that will provide a means of manipulation and facilitate operations in urban environments. The resulting fabricated arm described in this thesis weighs only 13 pounds, and is capable of holding 11 pounds fully outstretched, lifting objects such as tools, and it can open doors. It is also capable of being easily integrated with the IHMC / Bucknell University biped. This thesis provides an introduction to robots themselves, discusses the goals of the Bucknell Humanoid Robot Arm project, provides a background on some of the existing robots, and shows how the Bucknell Humanoid Robot Arm fits in with the studies that have been completed. After reading these studies, important items such as design trees and operational scenarios were completed. The completion of these items led to measurable specifications and later the design requirements and specifications. A significant contribution of this thesis to the robotics discipline involves the design of the actuator itself. The arm uses of individual, lightweight, compactly designed actuators to achieve desired capabilities and performance requirements. Many iterations were completed to get to the final design of each actuator. After completing the actuators, the design of the intermediate links and brackets was finalized. Completion of the design led to the development of a complex controls system which used a combination of Clanguage and Java.

Teleoperation of a 7 DOF humanoid robot arm using human arm accelerations and EMG signals

We present our work on tele-operating a complex humanoid robot with the help of bio-signals collected from the operator. The frameworks (for robot vision, collision avoidance and machine learning), developed in our lab, allow for a safe interaction with the environment, when combined. This even works with noisy control signals, such as, the operator’s hand acceleration and their electromyography (EMG) signals. These bio-signals are used to execute equivalent actions (such as, reaching and grasping of objects) on the 7 DOF arm.

Robot navigation using human cues: A robot navigation system for symbolic goal-directed exploration

In this paper we present for the first time a complete symbolic navigation system that performs goal-directed exploration to unfamiliar environments on a physical robot. We introduce a novel construct called the abstract map to link provided symbolic spatial information with observed symbolic information and actual places in the real world. Symbolic information is observed using a text recognition system that has been developed specifically for the application of reading door labels. In the study described in this paper, the robot was provided with a floor plan and a destination. The destination was specified by a room number, used both in the floor plan and on the door to the room. The robot autonomously navigated to the destination using its text recognition, abstract map, mapping, and path planning systems. The robot used the symbolic navigation system to determine an efficient path to the destination, and reached the goal in two different real-world environments. Simulation results show that the system reduces the time required to navigate to a goal when compared to random exploration.

A hybrid of modified PSO and local search on a multi-robot search system

Particle swarm optimization (PSO), a new population based algorithm, has recently been used on multi-robot systems. Although this algorithm is applied to solve many optimization problems as well as multi-robot systems, it has some drawbacks when it is applied on multi-robot search systems to find a target in a search space containing big static obstacles. One of these defects is premature convergence. This means that one of the properties of basic PSO is that when particles are spread in a search space, as time increases they tend to converge in a small area. This shortcoming is also evident on a multi-robot search system, particularly when there are big static obstacles in the search space that prevent the robots from finding the target easily; therefore, as time increases, based on this property they converge to a small area that may not contain the target and become entrapped in that area.Another shortcoming is that basic PSO cannot guarantee the global convergence of the algorithm. In other words, initially particles explore different areas, but in some cases they are not good at exploiting promising areas, which will increase the search time.This study proposes a method based on the particle swarm optimization (PSO) technique on a multi-robot system to find a target in a search space containing big static obstacles. This method is not only able to overcome the premature convergence problem but also establishes an efficient balance between exploration and exploitation and guarantees global convergence, reducing the search time by combining with a local search method, such as A-star.To validate the effectiveness and usefulness of algorithms,a simulation environment has been developed for conducting simulation-based experiments in different scenarios and for reporting experimental results. These experimental results have demonstrated that the proposed method is able to overcome the premature convergence problem and guarantee global convergence.

MPC controlled multirotor with suspended slung load: System architecture and visual load detection

There is an increased interest in the use of Unmanned Aerial Vehicles for load transportation from environmental remote sensing to construction and parcel delivery. One of the main challenges is accurate control of the load position and trajectory. This paper presents an assessment of real flight trials for the control of an autonomous multi-rotor with a suspended slung load using only visual feedback to determine the load position. This method uses an onboard camera to take advantage of a common visual marker detection algorithm to robustly detect the load location. The load position is calculated using an onboard processor, and transmitted over a wireless network to a ground station integrating MATLAB/SIMULINK and Robotic Operating System (ROS) and a Model Predictive Controller (MPC) to control both the load and the UAV. To evaluate the system performance, the position of the load determined by the visual detection system in real flight is compared with data received by a motion tracking system. The multi-rotor position tracking performance is also analyzed by conducting flight trials using perfect load position data and data obtained only from the visual system. Results show very accurate estimation of the load position (~5% Offset) using only the visual system and demonstrate that the need for an external motion tracking system is not needed for this task.

Declarative sensor knowledge in a robot monitoring system

Hardy, N. W., Barnes, D. P., Lee, M. (1987). Declarative sensor knowledge in a robot monitoring system. In: Languages for Sensor-Based Control in Robotics, Ulrich Rembold and Klaus H?rmann (eds), Springer-Verlag, p. 169-188.

VLSI architecture for an Underwater Robot Vision System

It is well known that image processing requires a huge amount of computation, mainly at low level processing where the algorithms are dealing with a great number of data-pixel. One of the solutions to estimate motions involves detection of the correspondences between two images. For normalised correlation criteria, previous experiments shown that the result is not altered in presence of nonuniform illumination. Usually, hardware for motion estimation has been limited to simple correlation criteria. The main goal of this paper is to propose a VLSI architecture for motion estimation using a matching criteria more complex than Sum of Absolute Differences (SAD) criteria. Today hardware devices provide many facilities for the integration of more and more complex designs as well as the possibility to easily communicate with general purpose processors

Parallel manipulators with a rotation-symmetric arm system

Parallel manipulators with a rotation-symmetric arm system possess all the typical advantages of parallel robots, such as high acceleration and high-accuracy positioning. Contrary to the majority of proposed parallel manipulators, the rotation-symmetric arm system leads to a large workspace in relation to the footprint of the manipulator. This paper focuses on a subclass of these manipulators with additional favorable qualities, including low inertia and high eigenfrequencies. These qualities are achieved using only 5-DOF lower arm links and by mounting all actuators on the nonmoving base column of the manipulator. The common feature of all previously proposed manipulators in this subclass is identified and several novel 3-DOF and 4-DOF members are introduced.

Kinematic analysis and workspace determination of hexarot-a novel 6-DOF parallel manipulator with a rotation-symmetric arm system

Parallel mechanisms possess several advantages such as the possibilities for high acceleration and high accuracy positioning of the end effector. However, most of the proposed parallel manipulators suffer from a limited workspace. In this paper, a novel 6-DOF parallel manipulator with coaxial actuated arms is introduced. Since parallel mechanisms have more workspace limitations compared to that of serial mechanisms, determination of the workspace in parallel manipulators is of the utmost importance. For finding position, angular velocity, and acceleration, in this paper, inverse and forward kinematics of the mechanism are studied and after presenting the workspace limitations, workspace analysis of the hexarot manipulator is performed by using MATLAB software. Next, using the obtained cloud of points from simulation, the overall borders of the workspace are illustrated. Finally, it is shown that this manipulator has the important benefits of combining a large positional workspace in relation to its footprint with a sizable range of platform rotations.