Autonomous vision-guided bi-manual grasping and manipulation

This paper describes the implementation, demonstration and evaluation of a variety of autonomous, vision-guided manipulation capabilities, using a dual-arm Baxter robot. Initially, symmetric coordinated bi-manual manipulation based on kinematic tracking algorithm was implemented on the robot to enable a master-slave manipulation system. We demonstrate the efficacy of this approach with a human-robot collaboration experiment, where a human operator moves the master arm along arbitrary trajectories and the slave arm automatically follows the master arm while maintaining a constant relative pose between the two end-effectors. Next, this concept was extended to perform dual-arm manipulation without human intervention. To this extent, an image-based visual servoing scheme has been developed to control the motion of arms for positioning them at a desired grasp locations. Next we combine this with a dynamic position controller to move the grasped object using both arms in a prescribed trajectory. The presented approach has been validated by performing numerous symmetric and asymmetric bi-manual manipulations at different conditions. Our experiments demonstrated 80% success rate in performing the symmetric dual-arm manipulation tasks; and 73% success rate in performing asymmetric dualarm manipulation tasks

Quality and productivity driven trajectory optimisation for robotic handling of compliant sheet metal parts in multi-press stamping lines

This paper investigates trajectory generation for multi-robot systems that handle compliant parts in order to minimise deformations during handling, which is important to reduce the risk of affecting the part’s dimensional quality. An optimisation methodology is proposed to generate deformation-minimal multi-robot coordinated trajectories for predefined robot paths and cycle-time. The novelty of the proposed optimisation methodology is that it efficiently estimates part deformations using a precomputed Response Surface Model (RSM), which is based on data samples generated by Finite Element Analysis (FEA) of the handled part and end-effector. The end-effector holding forces, plastic part deformations, collision-avoidance and multi-robot coordination are also considered as constraints in the optimisation model. The optimised trajectories are experimentally validated and the results show that the proposed optimisation methodology is able to significantly reduce the deformations of the part during handling, i.e. up to 12% with the same cycle-time in the case study that involves handling compliant sheet metal parts. This investigation provides insights into generating specialised trajectories for material handling of compliant parts that can systematically minimise part deformations to ensure final dimensional quality

Temporal models of motions and forces for Human-Robot Interactive manipulation

L'intérêt pour la robotique a débuté dans les années 70 et depuis les robots n'ont cessé de remplacer les humains dans l'industrie. L'automatisation à outrance n'apporte cependant pas que des avantages, car elle nécessite des environnements parfaitement contrôlés et la reprogrammation d'une tâche est longue et fastidieuse. Le besoin accru d'adaptabilité et de ré-utilisabilité des systèmes d'assemblage force la robotique à se révolutionner en amenant notamment l'homme et le robot à interagir. Ce nouveau type de collaboration permet de combiner les forces respectives des humains et des robots. Cependant l'homme ne pourra être inclus en tant qu'agent actif dans ces nouveaux espaces de travail collaboratifs que si l'on dispose de robots sûrs, intuitifs et facilement reprogrammables. C'est à la lumière de ce constat qu'on peut deviner le rôle crucial de la génération de mouvement pour les robots de demain. Pour que les humains et les robots puissent collaborer, ces derniers doivent générer des mouvements sûrs afin de garantir la sécurité de l'homme tant physique que psychologique. Les trajectoires sont un excellent modèle pour la génération de mouvements adaptés aux robots collaboratifs, car elles offrent une description simple et précise de l'évolution du mouvement. Les trajectoires dîtes souples sont bien connues pour générer des mouvements sûrs et confortables pour l'homme. Dans cette thèse nous proposons un algorithme de génération de trajectoires temps-réel basé sur des séquences de segments de fonctions polynomiales de degré trois pour construire des trajectoires souples. Ces trajectoires sont construites à partir de conditions initiales et finales arbitraires, une condition nécessaire pour que les robots soient capables de réagir instantanément à des événements imprévus. L'approche basée sur un modèle à jerk-contraint offre des solutions orientées performance: les trajectoires sont optimales en temps sous contraintes de sécurité. Ces contraintes de sécurité sont des contraintes cinématiques qui dépendent de la tâche et du contexte et doivent être spécifiées. Pour guider le choix de ces contraintes, nous avons étudié le rôle de la cinématique dans la définition des propriétés ergonomiques du mouvement. L'algorithme a également été étendu pour accepter des configurations initiales non admissibles permettant la génération de trajectoires sous contraintes cinématiques non constantes. Cette extension est essentielle dans le contexte des interactions physiques homme-robot, car le robot doit être capable d'adapter son comportement en temps-réel pour préserver la sécurité physique et psychologique des humains. Cependant considérer le problème de la génération de trajectoires ne suffit pas si on ne considère pas le contrôle. Le passage d'une trajectoire à une autre est un problème difficile pour la plupart des systèmes robotiques dans des contextes applicatifs réels. Pour cela, nous proposons une stratégie de contrôle réactif de ces trajectoires ainsi qu'une architecture construite autour de l'utilisation des trajectoires.It was in the 70s when the interest for robotics really emerged. It was barely half a century ago, and since then robots have been replacing humans in the industry. This robot-oriented solution doesn't come without drawbacks as full automation requires time-consuming programming as well as rigid environments. With the increased need for adaptability and reusability of assembly systems, robotics is undergoing major changes and see the emergence of a new type of collaboration between humans and robots. Human-Robot collaboration get the best of both world by combining the respective strengths of humans and robots. But, to include the human as an active agent in these new collaborative workspaces, safe and flexible robots are required. It is in this context that we can apprehend the crucial role of motion generation in tomorrow's robotics. For the emergence of human-robot cooperation, robots have to generate motions ensuring the safety of humans, both physical and physchological. For this reason motion generation has been a restricting factor to the growth of robotics in the past. Trajectories are excellent candidates in the making of desirable motions designed for collaborative robots, because they allow to simply and precisely describe the motions. Smooth trajectories are well known to provide safe motions with good ergonomic properties. In this thesis we propose an Online Trajectory Generation algorithm based on sequences of segment of third degree polynomial functions to build smooth trajectories. These trajectories are built from arbitrary initial and final conditions, a requirement for robots to be able to react instantaneously to unforeseen events. Our approach built on a constrained-jerk model offers performance-oriented solutions : the trajectories are time-optimal under safety constraints. These safety constraints are kinematic constraints that are task and context dependent and must be specified. To guide the choice of these constraints we investigated the role of kinematics in the definition of ergonomics properties of motions. We also extended our algorithm to cope with non-admissible initial configurations, opening the way to trajectory generation under non-constant motion constraints. This feature is essential in the context of physical Human-Robot Interactions, as the robot must adapt its behavior in real time to preserve both the physical and psychological safety of humans. However, only considering the trajectory generation problem is not enough and the control of these trajectories must be adressed. Switching from a trajectory to another is a difficult problem for most robotic systems in real applicative contexts. For this purpose we propose a strategy for the Reactive Control of these Trajectories as well as an architecture built around the use of trajectories

Design and Validation of a MR-compatible Pneumatic Manipulandum

The combination of functional MR imaging and novel robotic tools may provide unique opportunities to probe the neural systems underlying motor control and learning. Here, we describe the design and validation of a MR-compatible, 1 degree-of-freedom pneumatic manipulandum along with experiments demonstrating its safety and efficacy. We first validated the robot\u27s ability to apply computer-controlled loads about the wrist, demonstrating that it possesses sufficient bandwidth to simulate torsional spring-like loads during point-to-point flexion movements. Next, we verified the MR-compatibility of the device by imaging a head phantom during robot operation. We observed no systematic differences in two measures of MRI signal quality (signal/noise and field homogeneity) when the robot was introduced into the scanner environment. Likewise, measurements of joint angle and actuator pressure were not adversely affected by scanning. Finally, we verified device efficacy by scanning 20 healthy human subjects performing rapid wrist flexions against a wide range of spring-like loads. We observed a linear relationship between joint torque at peak movement extent and perturbation magnitude, thus demonstrating the robot\u27s ability to simulate spring-like loads in situ. fMRI revealed task-related activation in regions known to contribute to the control of movement including the left primary sensorimotor cortex and right cerebellum

Climbing and Walking Robots

Nowadays robotics is one of the most dynamic fields of scientific researches. The shift of robotics researches from manufacturing to services applications is clear. During the last decades interest in studying climbing and walking robots has been increased. This increasing interest has been in many areas that most important ones of them are: mechanics, electronics, medical engineering, cybernetics, controls, and computers. Today’s climbing and walking robots are a combination of manipulative, perceptive, communicative, and cognitive abilities and they are capable of performing many tasks in industrial and non- industrial environments. Surveillance, planetary exploration, emergence rescue operations, reconnaissance, petrochemical applications, construction, entertainment, personal services, intervention in severe environments, transportation, medical and etc are some applications from a very diverse application fields of climbing and walking robots. By great progress in this area of robotics it is anticipated that next generation climbing and walking robots will enhance lives and will change the way the human works, thinks and makes decisions. This book presents the state of the art achievments, recent developments, applications and future challenges of climbing and walking robots. These are presented in 24 chapters by authors throughtot the world The book serves as a reference especially for the researchers who are interested in mobile robots. It also is useful for industrial engineers and graduate students in advanced study

A practical method of reverse engineering and automatic path programming for robotic surface finishing

A method of robotic surface finishing is discussed. The method is question incorporates COTS (commercial of the shelf) technology

Toward Future Automatic Warehouses: An Autonomous Depalletizing System Based on Mobile Manipulation and 3D Perception

This paper presents a mobile manipulation platform designed for autonomous depalletizing tasks. The proposed solution integrates machine vision, control and mechanical components to increase flexibility and ease of deployment in industrial environments such as warehouses. A collaborative robot mounted on a mobile base is proposed, equipped with a simple manipulation tool and a 3D in-hand vision system that detects parcel boxes on a pallet, and that pulls them one by one on the mobile base for transportation. The robot setup allows to avoid the cumbersome implementation of pick-and-place operations, since it does not require lifting the boxes. The 3D vision system is used to provide an initial estimation of the pose of the boxes on the top layer of the pallet, and to accurately detect the separation between the boxes for manipulation. Force measurement provided by the robot together with admittance control are exploited to verify the correct execution of the manipulation task. The proposed system was implemented and tested in a simplified laboratory scenario and the results of experimental trials are reported