Simulation of Mechanical Systems With Multiple Frictional Contacts

There are several applications in robotics and manufacturing in which nominally rigid objects are subject to multiple frictional contacts with other objects. In most previous work, rigid body models have been used to analyze such systems. There are two fundamental problems with such an approach. Firstly, the use of frictional laws, such as Coulomb\u27s law, introduce inconsistencies and ambiguities when used in conjunction with the principles of rigid body dynamics. Secondly, hypotheses traditionally used to model frictional impacts can lead to solutions which violate principles of energy conservation. In this paper these problems are explained with the help of examples. A new approach to the simulation of mechanical systems with multiple, frictional constraints is proposed which is free of inconsistencies

Dynamics of Rigid Bodies Undergoing Multiple Frictional Contacts

There are several applications in robotics and manufacturing in which nominally rigid objects are subject to multiple frictional contacts with other objects. In most previous work, rigid body models have been used to analyze such systems. There are two fundamental problems with such an approach. Firstly, the use of frictional laws, such as Coulomb\u27s law, introduce inconsistencies and ambiguities when used in conjunction with the principles of rigid body dynamics. Secondly, hypotheses traditionally used to model frictional impacts can lead to solutions which violate principles of energy conservation. In this paper these problems are explained with the help of examples. A new approach to the simulation of mechanical systems with multiple, frictional constraints is proposed which is free of inconsistencies

Vibration as an aid in robotic peg-in-hole assembly

This dissertation presents an analytical and experimental investigation of vibration assisted engagement for parts mating. A dynamic model of assembly is established by using Lagrange\u27s equation for impact to derive impact equations for a robotic manipulator in peg-in-hole assembly. The model can be used to analyze part motion and contact force in the mating of parts by robots. The impact equations of a SCARA robot are derived using this model and utilized to investigate how robot configuration, insertion speed, chamfer angle, coefficient of restitution and other system parameters affect impulsive force and departure angle in the assembly of a peg with a chamfered hole in the presence of position errors. In the analytical investigation, how the vibration amplitude, vibration frequency, frequency ratio, phase angle, uncertainty and tolerance of the assembly system affect the engagement time is analyzed. An algorithm is developed to determine the required time for engagement given a set of assembly and vibration parameters. An intelligent force-based approach is used in conjunction with this algorithm to aid mating of parts and is implemented in experiments to verify analytical results

Stiffness Control in Robotic Assembly Tasks

The peg in hole problem has been heavily studied in literature as a simple model to analyze assembly scenarios. Due to advances in robotic hardware and research on robots which are safe to humans, many of the models and simplifications present in literature don't apply anymore or present poor approximations for modern robots with impedance controllers. In the following work the problem of a peg-in-hole insertion with a impedance controlled robot will be tackled, and simple rules to choose optimal cartesian stiffnesses are presented. The same rules are then applied to solve the problem of optimizing stiffnesses for a VSA robot, where a desired cartesian stiffness cannot generally be obtained. A method to chose weights for the simple weighted minimization of the distance between the desired and obtained cartesian stiffnesses is then proposed, and the results of both approaches are compared by using a robot with deboupled joint stiffness control. Lastly, results of a bimanual insertion using a real VSA robot are proposed

Task planning with uncertainty for robotic systems

In a practical robotic system, it is important to represent and plan sequences of operations and to be able to choose an efficient sequence from them for a specific task. During the generation and execution of task plans, different kinds of uncertainty may occur and erroneous states need to be handled to ensure the efficiency and reliability of the system. An approach to task representation, planning, and error recovery for robotic systems is demonstrated. Our approach to task planning is based on an AND/OR net representation, which is then mapped to a Petri net representation of all feasible geometric states and associated feasibility criteria for net transitions. Task decomposition of robotic assembly plans based on this representation is performed on the Petri net for robotic assembly tasks, and the inheritance of properties of liveness, safeness, and reversibility at all levels of decomposition are explored. This approach provides a framework for robust execution of tasks through the properties of traceability and viability. Uncertainty in robotic systems are modeled by local fuzzy variables, fuzzy marking variables, and global fuzzy variables which are incorporated in fuzzy Petri nets. Analysis of properties and reasoning about uncertainty are investigated using fuzzy reasoning structures built into the net. Two applications of fuzzy Petri nets, robot task sequence planning and sensor-based error recovery, are explored. In the first application, the search space for feasible and complete task sequences with correct precedence relationships is reduced via the use of global fuzzy variables in reasoning about subgoals. In the second application, sensory verification operations are modeled by mutually exclusive transitions to reason about local and global fuzzy variables on-line and automatically select a retry or an alternative error recovery sequence when errors occur. Task sequencing and task execution with error recovery capability for one and multiple soft components in robotic systems are investigated

On Probabilistic Strategies for Robot Tasks

Robots must act purposefully and successfully in an uncertain world. Sensory information is inaccurate or noisy, actions may have a range of effects, and the robot's environment is only partially and imprecisely modeled. This thesis introduces active randomization by a robot, both in selecting actions to execute and in focusing on sensory information to interpret, as a basic tool for overcoming uncertainty. An example of randomization is given by the strategy of shaking a bin containing a part in order to orient the part in a desired stable state with some high probability. Another example consists of first using reliable sensory information to bring two parts close together, then relying on short random motions to actually mate the two parts, once the part motions lie below the available sensing resolution. Further examples include tapping parts that are tightly wedged, twirling gears before trying to mesh them, and vibrating parts to facilitate a mating operation