Sequential and Simultaneous Algorithms to Solve the Collision-Free Trajectory Planning Problem for Industrial Robots – Impact of Interpolation Functions and the Characteristics of the Actuators on Robot Performance

This paper has been possible thanks to the funding of Science and Innovation Ministry of the Spain Government by means of the Researching and Technologic Development Project DPI2010-20814-C02-01 (IDEMOV).Rubio Montoya, FJ.; Valero Chuliá, FJ.; Besa Gonzálvez, AJ.; Pedrosa Sanchez, AM. (2012). Sequential and Simultaneous Algorithms to Solve the Collision-Free Trajectory Planning Problem for Industrial Robots ¿ Impact of Interpolation Functions and the Characteristics of the Actuators on Robot Performance. En Robotic Systems - Applications, Control and Programming. InTech. 591-610. doi:10.5772/25970S59161

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

Soft Motion Trajectory Planner for Service Manipulator Robot

Human interaction introduces two main constraints: Safety and Comfort. Therefore service robot manipulator can't be controlled like industrial robotic manipulator where personnel is isolated from the robot's work envelope. In this paper, we present a soft motion trajectory planner to try to ensure that these constraints are satisfied. This planner can be used on-line to establish visual and force control loop suitable in presence of human. The cubic trajectories build by this planner are good candidates as output of a manipulation task planner. The obtained system is then homogeneous from task planning to robot control. The soft motion trajectory planner limits jerk, acceleration and velocity in cartesian space using quaternion. Experimental results carried out on a Mitsubishi PA10-6CE arm are presented

Minimum-time path planning for robot manipulators using path parameter optimization with external force and frictions

This paper presents a new minimum-time trajectory planning method which consists of a desired path in the Cartesian space to a manipulator under external forces subject to the input voltage of the actuators. Firstly, the path is parametrized with an unknown parameter called a path parameter. This parameter is considered a function of time and an unknown parameter vector for optimization. Secondly, the optimization problem is converted into a regular parameter optimization problem, subject to the equations of motion and limitations in angular velocity, angular acceleration, angular jerk, input torques of actuators’, input voltage and final time, respectively. In the presented algorithm, the final time of the task is divided into known partitions, and the final time is an additional unknown variable in the optimization problem. The algorithm attempts to minimize the final time by optimizing the path parameter, thus it is parametrized as a polynomial of time with some unknown parameters. The algorithm can have a smooth input voltage in an allowable range; then all motion parameters and the jerk will remain smooth. Finally, the simulation study shows that the presented approach is efficient in the trajectory planning for a manipulator that wants to follow a Cartesian path. In simulations, the constraints are respected, and all motion variables and path parameters remain smooth