Failure detection and correction is essential in robust systems. In robotics, failure detection has focused on traditional parts assembly, tool breakage, and threaded fastener assembly. However, not much work has focused on sub-mode failure classification. This is an important step in order to provide accurate failure recovery. Our work implemented a novel failure characterization scheme for cantilever snap assemblies. The approach identified exemplars that characterized salient features for specific deviations from a nominal trajectory. Then, a rule based approach with statistical measures was used to identify failure and classify failure sub-modes. Failure sub-mode classification was evaluated by using a reliability measure. Our work classified failure deviations with 88% accuracy. Varying success was experienced in correlating failure deviation modes. Cases with only 1-deviation had 86% accuracy, cases with 2-deviations had 67% accuracy, and cases with 3 deviations had 55% accuracy. Our work is an important step in failure characterization of complex geometrical parts and serves as a stepping stone to enact failure recovery.

In this paper, the author deals with a formulation of packing several kinds of goods, which are separately packed into separated areas in a container. In order to minimize the size of a container, each volume of each kind of goods (“block”) should be minimized. In this minimization, packing procedures should be taken into account in order to determine feasibility of packing by a robot. In this paper, packing procedures are generated automatically by using the proposed method.

This paper proposes an object placement planner for a grasped object during pick-and-place tasks. The proposed planner automatically determines the pose of an object stably placed near a user assigned point on an environment surface. The proposed method first constructs a polygon model of the surrounding environment, and then clusters the polygon model of both the environment and the object where each cluster is approximated by a planar region. The placement of the object can be determined by selecting a pair of clusters between the object and the environment. We further impose several conditions to determine the pose of the object placed on the environment. We show that we can determine the position/orientation of the object placed on the environment for several cases such as hanging a mug cup on a bar. The effectiveness of the proposed research is confirmed through several numerical examples.

Snap assembly automation remains a challenging task. While progress is being made in localization of parts, force controllers, and control strategies, little work has been done to help the robot reason about its current state, such that if necessary, the robot can assume corrective actions to accomplish the task. Error prone situations caused by the unexpected motion of parts, localization errors, jamming or wedging, cannot be solved by force controllers alone. For this reason we propose a snap assemblies verification system for cantilever-snap fasteners. The verification works in concert with a control strategy that makes use of constraint designs embedded in the snap parts' physical design. The constrained assembly motion generates similar sensory-signal patterns across trials that facilitates force signal discrimination into higher level abstractions of intuitive behavior. This work's contribution is the design of a hierarchical taxonomy for cantilever-snap verification based on increasingly abstract layers that encode relative-change in the task's force signatures. A five-layered taxonomy is built on the concept that relative-change patterns can be classified through a small category set and aided by contextual information. The verification system yielded human apropos intuitive categorizations of task behavior for every state and effectively determined the assembly result. This simple yet effective approach will be expanded to perform probabilistic online system verification to aid in fault tolerance and the automation of cantilever-based snap assemblies.

In this paper, we propose a task skill transfer method using a bilateral teleoperation. We assume that a task skill for a complicated motion is described by the suitable trajectory of the impedance center. Thus, a important point is how to get the suitable trajectory of the impedance center. In our method, the suitable trajectory is got from results of bilateral teleoperation. In the bilateral teleoperation, an operator constructs a motion procedure able to execute the task. The suitable trajectory of the impedance center is calculated from the position and the force data in the teleoperation experiment. A basic element of the task skill is composed of an initial condition, a task skill motion and a final condition. The initial and final conditions are described by values of both sensor and tip position. The task skill motion is described by a hybrid impedance/force control. To demonstrate how to use of our method, we choose the nut attachment task as an example

"Teaching by demonstration" is a method to generate a robot program that makes a robot do the same task as the task that a human operator demonstrates. We have developed a "teaching by demonstration in VR" system (TbDinVR) which automatically generates a robot program to work in the real world after a task is demonstrated by an operator in the virtual world. In this paper, we have explained necessary and sufficient condition for states in a task description, advantages of using state-based TbDinVR system, and a simulator for determining parameters of skill primitives by using sensor simulation in VR and a random search technique in detail. We have shown an experimental result and visualization of that result.

"Teaching by Demonstration" is a method of generating a robot program that makes a robot do the same task as the task that a human operator demonstrates. We have developed a "teaching by demonstration in VR" system that automatically generates a robot program to work in the red world after a task is demonstrated by an operator in the virtual world. This system generates a program that detects each contact state extracted from demonstration in VR and produces it by skillful motion primitives. We find that some types of motion that are included in the recorded motion given by a human operator in the VR in teaching stage cannot be realized in the execution stage if the robot tries to do the same task by using the human demonstration data even on a contact state level. In this paper, based an our observation that a human has the skill wherein contact state transitions are made non-deterministically, we propose a method of dealing with one of the important non-deterministic motions, "non-deterministic search type motion" Experimental results show the feasibility of the method.

Describes a unified method for integrating different kinds of sensor-based control. We introduced "control space", which is smoothly related to actuator space. Each sensor-based control law is described in the control space. The integration is done automatically by mapping the control space to the actuator space based on local linear relations between them. We also proposed the multi-agent-based implementation of the control system. Simulation and experiment show the effectiveness of this new method.

Teaching by demonstration is a method to generate a robot program that makes a robot do the same task as the task which a human operator demonstrates. The author developed a teaching by demonstration in VR system which automatically generates a robot program to work in the real world after a task is demonstrated by an operator in the virtual world. This system deals with a task of controlling contact states between bodies like the assembly task. When one body is not in contact with another, not only contact states but also other new states which can specify more general arrangement of the bodies are necessary in order to make the robot more skilful. The author introduced a virtual smallface (VSF) and an artificial constrained motion primitive (ACMP) for this purpose. A virtual polyhedron for constrained motion (VPCM) is newly introduced in order to implement more general ACMPs. An operator more easily and generally defines new states of the task by using VSFs and VPCMs, since VSFs are used to define intuitively new states of a task and since (virtual) contact states between VPCMs are also used as the new states.

The paper describes an integrated teleoperation system for maintenance tasks with planning functions based on manipulation skills. We embed planning functions into a telerobotics system to make the system more flexible and robust. A motion teaching system based on contact state transition, a geometric modeling system using teaching trees, and a task execution system based on manipulation skills are integrated. The design concept of the system and essential technologies are described. An experimental task is explained to demonstrate the efficiency of the telerobotics system.

The authors studied the planning for wire obstacle avoidance by manipulators. It is difficult to know the location and direction of an obstacle with an ultrasonic sensor, since distance is the only information provided by the sensor. The authors propose here a method for estimating the location and direction of a wire obstacle by using multiple items of information on distance. The authors report the results of simulation of path modification by detecting wire obstacles based on the proposed method.

When the desired motion of the grasped object is given or planned, the coordination of motion of the manipulator and manipulation with its gripper is needed in order to achieve the desired motion of the object. In this paper, we have defined "graspability", "manipulability", and "virtual gripper". These concepts are necessary to deal with the geometric relation between a dexterous hand and its grasped object in the planning process and designing process. Since the coordination of motion of the manipulator and manipulation of its gripper is needed in order to achieve the desired motion of the grasped object, we have developed an algorithm that generates these coordinated motions: the path of the manipulator and the manipulation path of the object with respect to the coordinate frame of the gripper. This paper describes "graspability", "manipulability", "virtual gripper", an algorithm that generates the coordinated motions, and estimation of a "manipulable region" of a dexterous gripper which is needed in a specific task.

We have been developing prototypes of teleoperation systems via a standard protocol with a standard human interface, where VRML2.0 is employed as the protocol and a Web browser as the human interface. Using a Web browser, an operator can plan motions of objects interactively on a manipulation simulator with a world model which was sent from a remote site via VRML. The employment of a standard protocol and human interface enables our teleoperation system to be used by non-specialists from any Internet site, or by anyone from anywhere, without installing any specific software on the client side a priori.

We have developed a teaching system based on the assumption that the assembly task is a series of operations for achieving a target contact state among objects through changing their contact states. The features of our system are as follows: 1) teaching data for fine motion is extracted from a demonstration by an operator in a virtual world, 2) the operator can edit intermediate expressions on a display, 3) intermediate expressions can be used by any robot system with a skill library which has the ability to achieve the corresponding contact states. This paper describes the configuration of the system, program generation using intermediate expressions and a skill library to achieve each contact state.

Since general automatic assembly motion planning using a geometric CAD model is computationally difficult, automation of a general assembly task is not feasible. However, if a human operator roughly specifies an assembly motion, the remainder of the process except for planning can be automated. We construct a teaching system for assembly tasks according to the above concept. This paper describes our teaching system for assembly tasks by using a position/force simulator. We show how to construct the position/force simulator and analyse the hybrid position/force control which is needed when dealing with general rotational motion. We show the example of extracting a sequence of contact state transitions from the motion which the operator performs in the position simulator of our system. The sequence of contact states automatically extracted from the motion shown by the operator makes it feasible to achieve an error-tolerant automated assembly motion. If a sequence of contact states is obtained, studies of the automatic assembly task system can progress based upon this information.

Introduces the concept of configuration patches (C-patches) for representing configurations of a polyhedral robot in a point-point contact with polyhedral obstacles, and proposes an approach called the inverse mapping method for computing an approximate representation with cubic cells of the configuration space (C-space) of the robot. The configuration patches represented in a local coordinate system, have simple geometric shapes like paralleltopes. The inverse mapping method constructs the approximation of a C-space by quantizing the C-patches in the local coordinate system. There is no need to check any intersection among the robot and the obstacles. The only process needed is a coordinate transformation from discrete points on the C-patches to configurations of the robot.