Regrasp Planning using 10,000s of Grasps

This paper develops intelligent algorithms for robots to reorient objects. Given the initial and goal poses of an object, the proposed algorithms plan a sequence of robot poses and grasp configurations that reorient the object from its initial pose to the goal. While the topic has been studied extensively in previous work, this paper makes important improvements in grasp planning by using over-segmented meshes, in data storage by using relational database, and in regrasp planning by mixing real-world roadmaps. The improvements enable robots to do robust regrasp planning using 10,000s of grasps and their relationships in interactive time. The proposed algorithms are validated using various objects and robots

Stable Prehensile Pushing: In-Hand Manipulation with Alternating Sticking Contacts

This paper presents an approach to in-hand manipulation planning that exploits the mechanics of alternating sticking contact. Particularly, we consider the problem of manipulating a grasped object using external pushes for which the pusher sticks to the object. Given the physical properties of the object, frictional coefficients at contacts and a desired regrasp on the object, we propose a sampling-based planning framework that builds a pushing strategy concatenating different feasible stable pushes to achieve the desired regrasp. An efficient dynamics formulation allows us to plan in-hand manipulations 100-1000 times faster than our previous work which builds upon a complementarity formulation. Experimental observations for the generated plans show that the object precisely moves in the grasp as expected by the planner. Video Summary -- youtu.be/qOTKRJMx6HoComment: IEEE International Conference on Robotics and Automation 201

Achieving reliability using behavioural modules in a robotic assembly system

The research in this thesis looks at improving the reliability of robotic as¬ sembly while still retaining the flexibility to change the system to cope with dif¬ ferent assemblies. The lack of a truly flexible robotic assembly system presents a problem which current systems have yet to overcome. An experimental sys¬ tem has been designed and implemented to demonstrate the ideas presented in this work. Runs of this system have also been performed to test and assess the scheme which has been developed.The Behaviour-based SOMASS system looks at decomposing the task into modular units, called Behavioural Modules, which reliably perform the as¬ sembly task by using variation reducing strategies. The thesis work looks at expanding this framework to produce a system which relaxes the constraints of complete reliability within a Behavioural Module by embedding these in a re¬ liable system architecture. This means that Behavioural Modules do not have to guarantee to successfully perform their given task but instead can perform it adequately, with occasional failures dealt with by the appropriate introduction of alternative actionsTo do this, the concepts of Exit States, the Ideal Execution Path, and Alter¬ native Execution Paths have been described. The Exit State of a Behavioural Module gives an indication of the control path which has actually been taken during its execution. This information, along with appropriate information available to the execution system (such as sensor and planner data), allows the Ideal Execution Path and Alternative Execution Paths to be defined. These show, respectively, the best control path through the system (as determined by the system designer) and alternative control routes which can be taken when necessary

Automatic generation of robot and manual assembly plans using octrees

This paper aims to investigate automatic assembly planning for robot and manual assembly. The octree decomposition technique is applied to approximate CAD models with an octree representation which are then used to generate robot and manual assembly plans. An assembly planning system able to generate assembly plans was developed to build these prototype models. Octree decomposition is an effective assembly planning tool. Assembly plans can automatically be generated for robot and manual assembly using octree models. Research limitations/implications - One disadvantage of the octree decomposition technique is that it approximates a part model with cubes instead of using the actual model. This limits its use and applications when complex assemblies must be planned, but in the context of prototyping can allow a rough component to be formed which can later be finished by hand. Assembly plans can be generated using octree decomposition, however, new algorithms must be developed to overcome its limitations

On CAD Informed Adaptive Robotic Assembly

We introduce a robotic assembly system that streamlines the design-to-make workflow for going from a CAD model of a product assembly to a fully programmed and adaptive assembly process. Our system captures (in the CAD tool) the intent of the assembly process for a specific robotic workcell and generates a recipe of task-level instructions. By integrating visual sensing with deep-learned perception models, the robots infer the necessary actions to assemble the design from the generated recipe. The perception models are trained directly from simulation, allowing the system to identify various parts based on CAD information. We demonstrate the system with a workcell of two robots to assemble interlocking 3D part designs. We first build and tune the assembly process in simulation, verifying the generated recipe. Finally, the real robotic workcell assembles the design using the same behavior