This paper presents a manipulation planning algorithm for robots to reorient objects. It automatically finds a sequence of robot motion that manipulates and prepares an object for specific tasks. Examples of the preparatory manipulation planning problems include reorienting an electric drill to cut holes, reorienting workpieces for assembly, and reorienting cargo for packing, etc. The proposed algorithm could plan single and dual arm manipulation sequences to solve the problems. The mechanism under the planner is a regrasp graph which encodes grasp configurations and object poses. The algorithms search the graph to find a sequence of robot motion to reorient objects. The planner is able to plan both single and dual arm manipulation. It could also automatically determine whether to use a single arm, dual arms, or their combinations to finish given tasks. The planner is examined by various humanoid robots like Nextage, HRP2Kai, HRP5P, etc., using both simulation and real-world experiments.
There are also lots of studies on dual-arm or multi-arm preparatory manipulation planning. For example, @cite_30 used predefined grasps to plan sequential manipulation for multiple manipulators in early time. @cite_17 applied the grasp-placement tables developed by @cite_14 to dual-arm robots. @cite_22 used decomposition to plan grasps and implemented dual-arm regrasp of complicated mesh models. Graphs, instead of grasp-placement tables, were used in the planner. @cite_31 presented regrasp and hand-over planning of dual-arm robots across multi-modal configuration spaces, and implemented a practical system in @cite_8 . Details of multi-modal motion planning could be found in @cite_0 , which made a concrete description of the concept and presented several implementations. More recent work like @cite_9 used dual-arm sequential manipulation planning to wrap up the fabric. It is also quite relevant except that reorienting directions are constrained by the wrapping heuristics. @cite_10 , @cite_11 , and Suarez- @cite_29 respectively applied integral prehensile and non-prehensile sequential dual-arm motion planning to the preparatory manipulation of a chair. @cite_7 presented a framework for simultaneous handover and visual recognition.
@cite_30 @cite_14 @cite_11 @cite_22 @cite_7 @cite_8 @cite_9 @cite_29 @cite_0 @cite_31 @cite_10 @cite_17
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We apply manipulation planning to computer animation. A new path planner is presented that automatically computes the collision-free trajectories for several cooperating arms to manipulate a movable object between two configurations. This implemented planner is capable of dealing with complicated tasks where regrasping is involved. In addition, we present a new inverse kinematics algorithm for the human arms. This algorithm is utilized by the planner for the generation of realistic human arm motions as they manipulate objects. We view our system as a tool for facilitating the production of animation. Closed kinematic chains are created whenever multiple robot arms concurrently manipulate a single object. The closed-chain constraint, when coupled with robot joint limits, dramatically changes the connectivity of the configuration space. We propose a regrasping move, termed “IK-switch,” which allows efficiently bridging components of the configuration space that are otherwise mutually disconnected. This move, combined with several other developments, such as a method to stabilize the manipulated object using the environment, a new tree structure, and a compliant control scheme, enables us to address complex closed-chain manipulation tasks, such as flipping a chair frame, which is otherwise impossible to realize using existing multi-arm planning methods. This paper proposes a planning framework to deal with the problem of computing the motion of a robot with dual arm hand, during an object pick-and-place task. We consider the situation where the start and goal configurations of the object constrain the robot to grasp the object with one hand, to give it to the other hand, before placing it in its final configuration. To realize such a task, the proposed framework treats the grasp computation, for one or two multi-fingered hands, of an arbitrarily-shaped object, the exchange configuration and finally the motion of the robot arms and body. In order to improve the planner performance, a context-independent grasp list is computed offline for each hand and for the given object as well as computed offline roadmap that will be adapted according to the environment composition. Simulation results show the planner performance on a complex scenario. This research develops a robotic vision and manipulation technologies for random bin-picking. Especially, we focus on the manipulation technology where a dual-arm manipulator first picks up an object from the pile, then regrasps it from the right hand to the left hand, and finally places it to the fixture. We first explain an overview of our research project. Then, we explain about the grasp manipulation planner for a dual-arm manipulator. Here, our grasp planner is well applied for objects which can be approximated by multiple cylinders. Also, our pick-and-place planner can effectively find a regrasping posture of an object. In addition to the manipulation technology, we briefly explain about our vision technology to measure the position orientation of an object. Finally, to show the effectiveness of our proposed approach, we show an experimental result of a dual-arm manipulator. This paper proposes a motion-planning method for a wrapping-with-fabric task. To wrap, robots require not only offhand paths (which represent the movement of a grasping point on fabric) but also actual robot motion. When a robot handles fabric, it must consider the range of motion and collisions. To overcome such limitations, the robot must pass fabric inter- and intra-hand. The proposition is based on the reliability of its movements. The method may be used to plan a combination of inter- and intra-hand passing motions to generate the basic movements for wrapping along an offhand path. Experiments show how, by using the proposed planning method, a dual-arm robot can wrap an L-shaped pipe. A pick-and-place operation in a 3-dimensional environment is a basic operation for humans and multi-purpose manipulators. However, there may be a difficult problem for such manipulators. Especially, if the object cannot be moved with a single grasp, regrasping, which can be a time-consuming process, should be carried out. Regrasping, given initial and final poses of the target object, is a construction of sequential transition of object poses that are compatible with two poses in the point of grasp configuration. This paper presents a novel approach for solving the regrasp problem. The approach consists of a preprocessing and a planning stage. Preprocessing, which is done only once for a given robot, generates a look-up table which has information on kinematically feasible task space of the end-effector throughout the entire workspace. Then, using this table, the planning automatically determines a possible intermediate location, pose and regrasp sequence leading from the pick-up to put-down grasp. With a redundant robot, it is shown experimentally that the presented method is complete in the entire workspace and can be implemented in real-time applications due to rapid regrasp planning time. The regrasp planner was combined with an existing path.