Path planning for robotic truss assembly

A new Potential Fields approach to the robotic path planning problem is proposed and implemented. Our approach, which is based on one originally proposed by Munger, computes an incremental joint vector based upon attraction to a goal and repulsion from obstacles. By repetitively adding and computing these 'steps', it is hoped (but not guaranteed) that the robot will reach its goal. An attractive force exerted by the goal is found by solving for the the minimum norm solution to the linear Jacobian equation. A repulsive force between obstacles and the robot's links is used to avoid collisions. Its magnitude is inversely proportional to the distance. Together, these forces make the goal the global minimum potential point, but local minima can stop the robot from ever reaching that point. Our approach improves on a basic, potential field paradigm developed by Munger by using an active, adaptive field - what we will call a 'flexible' potential field. Active fields are stronger when objects move towards one another and weaker when they move apart. An adaptive field's strength is individually tailored to be just strong enough to avoid any collision. In addition to the local planner, a global planning algorithm helps the planner to avoid local field minima by providing subgoals. These subgoals are based on the obstacles which caused the local planner to fail. A best-first search algorithm A* is used for graph search

Nonlinear control of multiple mobile manipulator robots transporting a rigid object in coordination

This doctoral thesis proposes and validates experimentally nonlinear control strategies for a group of mobile manipulator robots transporting a rigid object in coordination. This developed approach ensures trajectory tracking in Cartesian space in the presence of parameter uncertainty and undesirable disturbances. The objective of the creation of robots in the early sixties was to relieve man of certain hard jobs such as: handling a heavy object, and repetitive tasks which are often tiring or even sometimes infeasible manually. Following this situation, several types of manipulator robots were created. Naturally, the need for robots having both locomotion and manipulation capabilities has led to the creation of the mobile manipulators. Typical examples of mobile manipulators, more or less automated, are the cranes mounted on trucks , the satellite arms, the deep-sea exploration submarines, or extra-planetary exploration vehicles. Some operations requiring the handling of a heavy object are difficult to achieve by a single mobile manipulator. These operations require a coordination of several mobile manipulators to move or transport a heavy object in common. However, this complicates the robotic system as its control design complexity increases greatly. The problem of controlling the mechanical system forming a closed kinematic chain mechanism lies in the fact that it imposes a set of kinematic constraints on the coordination of the position and velocity of the mobile manipulator. Therefore, there is a reduction in the degrees of freedom for the entire system. Further, the internal forces of the object produced by all mobile manipulators should be controlled. This thesis work was focused on developing a consistent control technique for a group of mobile manipulator robots executing a task in coordination. Different nonlinear controllers were simulated and experimentally applied to multiple mobile manipulator system transporting a rigid object in coordination. To achieve all objectives of this thesis, as a first step, an experimental platform was developed and mounted in the laboratory of GREPCI-ETS to implement and validate the different designed control laws. In the second step, several adaptive coordinated motion/force tracking control laws were applied, ensuring that the desired trajectory can excellently tracked under uncertainties parameters and disturbances

Proceedings of the NASA Conference on Space Telerobotics, volume 3

The theme of the Conference was man-machine collaboration in space. The Conference provided a forum for researchers and engineers to exchange ideas on the research and development required for application of telerobotics technology to the space systems planned for the 1990s and beyond. The Conference: (1) provided a view of current NASA telerobotic research and development; (2) stimulated technical exchange on man-machine systems, manipulator control, machine sensing, machine intelligence, concurrent computation, and system architectures; and (3) identified important unsolved problems of current interest which can be dealt with by future research

Modeling, Analysis, and Control of a Mobile Robot for \u3ci\u3eIn Vivo\u3c/i\u3e Fluoroscopy of Human Joints during Natural Movements

In this dissertation, the modeling, analysis and control of a multi-degree of freedom (mdof) robotic fluoroscope was investigated. A prototype robotic fluoroscope exists, and consists of a 3 dof mobile platform with two 2 dof Cartesian manipulators mounted symmetrically on opposite sides of the platform. One Cartesian manipulator positions the x-ray generator and the other Cartesian manipulator positions the x-ray imaging device. The robotic fluoroscope is used to x-ray skeletal joints of interest of human subjects performing natural movement activities. In order to collect the data, the Cartesian manipulators must keep the x-ray generation and imaging devices accurately aligned while dynamically tracking the desired skeletal joint of interest. In addition to the joint tracking, this also requires the robotic platform to move along with the subject, allowing the manipulators to operate within their ranges of motion. A comprehensive dynamic model of the robotic fluoroscope prototype was created, incorporating the dynamic coupling of the system. Empirical data collected from an RGB-D camera were used to create a human kinematic model that can be used to simulate the joint of interest target dynamics. This model was incorporated into a computer simulation that was validated by comparing the simulation results with actual prototype experiments using the same human kinematic model inputs. The computer simulation was used in a comprehensive dynamic analysis of the prototype and in the development and evaluation of sensing, control, and signal processing approaches that optimize the subject and joint tracking performance characteristics. The modeling and simulation results were used to develop real-time control strategies, including decoupling techniques that reduce tracking error on the prototype. For a normal walking activity, the joint tracking error was less than 20 mm, and the subject tracking error was less than 140 mm

Proceedings of the NASA Conference on Space Telerobotics, volume 2

These proceedings contain papers presented at the NASA Conference on Space Telerobotics held in Pasadena, January 31 to February 2, 1989. The theme of the Conference was man-machine collaboration in space. The Conference provided a forum for researchers and engineers to exchange ideas on the research and development required for application of telerobotics technology to the space systems planned for the 1990s and beyond. The Conference: (1) provided a view of current NASA telerobotic research and development; (2) stimulated technical exchange on man-machine systems, manipulator control, machine sensing, machine intelligence, concurrent computation, and system architectures; and (3) identified important unsolved problems of current interest which can be dealt with by future research

Enhanced online programming for industrial robots

The use of robots and automation levels in the industrial sector is expected to grow, and is driven by the on-going need for lower costs and enhanced productivity. The manufacturing industry continues to seek ways of realizing enhanced production, and the programming of articulated production robots has been identified as a major area for improvement. However, realizing this automation level increase requires capable programming and control technologies. Many industries employ offline-programming which operates within a manually controlled and specific work environment. This is especially true within the high-volume automotive industry, particularly in high-speed assembly and component handling. For small-batch manufacturing and small to medium-sized enterprises, online programming continues to play an important role, but the complexity of programming remains a major obstacle for automation using industrial robots. Scenarios that rely on manual data input based on real world obstructions require that entire production systems cease for significant time periods while data is being manipulated, leading to financial losses. The application of simulation tools generate discrete portions of the total robot trajectories, while requiring manual inputs to link paths associated with different activities. Human input is also required to correct inaccuracies and errors resulting from unknowns and falsehoods in the environment. This study developed a new supported online robot programming approach, which is implemented as a robot control program. By applying online and offline programming in addition to appropriate manual robot control techniques, disadvantages such as manual pre-processing times and production downtimes have been either reduced or completely eliminated. The industrial requirements were evaluated considering modern manufacturing aspects. A cell-based Voronoi generation algorithm within a probabilistic world model has been introduced, together with a trajectory planner and an appropriate human machine interface. The robot programs so achieved are comparable to manually programmed robot programs and the results for a Mitsubishi RV-2AJ five-axis industrial robot are presented. Automated workspace analysis techniques and trajectory smoothing are used to accomplish this. The new robot control program considers the working production environment as a single and complete workspace. Non-productive time is required, but unlike previously reported approaches, this is achieved automatically and in a timely manner. As such, the actual cell-learning time is minimal

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored