Andrew Spielberg

Multi-robot grasp planning for sequential assembly operations

This paper addresses the problem of finding robot configurations to grasp assembly parts during a sequence of collaborative assembly operations. We formulate the search for such configurations as a constraint satisfaction problem (CSP). Collision constraints in an operation and transfer constraints between operations determine the sets of feasible robot configurations. We show that solving the connected constraint graph with off-the-shelf CSP algorithms can quickly become infeasible even for a few sequential assembly operations. We present an algorithm which, through the assumption of feasible regrasps, divides the CSP into independent smaller problems that can be solved exponentially faster. The algorithm then uses local search techniques to improve this solution by removing a gradually increasing number of regrasps from the plan. The algorithm enables the user to stop the planner anytime and use the current best plan if the cost of removing regrasps from the plan exceeds the cost of executing those regrasps. We present simulation experiments to compare our algorithms performance to a naive algorithm which directly solves the connected constraint graph. We also present a real robot system which uses the output of our planner to grasp and bring parts together in assembly configurations.

Towards coordinated precision assembly with robot teams

We present a system in which a flexible team of robots coordinates to assemble large, complex, and diverse structures autonomously. Our system operates across a wide range of spatial scales and tolerances, using a hierarchical perception architecture. For the successful execution of very precise assembly operations under initial uncertainty, our system starts with high-field of view but low accuracy sensors, and gradually uses low field-of-view but high accuracy sensors. Our system also uses a failure detection and recovery system, integrated with this hierarchical perception architecture: upon losing track of a feature, our system retracts to using high-field of view systems to re-localize. Additionally, we contribute manipulation skills and tools necessary to assemble large structures with high precision. First, the team of robots coordinates to transport large assembly parts which are too heavy for a single robot to carry. Second, we develop a new tool which is capable of co-localizing holes and fasteners for robust insertion and fastening. We present real robot experiments where we measure the contribution of the hierarchical perception and failure recovery approach to the robustness of our system. We also present an extensive set of experiments where our robots successfully insert all 80 of the attempted fastener insertion operations.

Interactive robogami: An end-to-end system for design of robots with ground locomotion

This paper aims to democratize the design and fabrication of robots, enabling people of all skill levels to make robots without needing expert domain knowledge. Existing work in computational design and rapid fabrication has explored this question of customization for physical objects but so far has not been able to conquer the complexity of robot designs. We have developed Interactive Robogami, a tool for composition-based design of ground robots that can be fabricated as flat sheets and then folded into 3D structures. This rapid prototyping process enables users to create lightweight, affordable, and materially versatile robots with short turnaround time. Using Interactive Robogami, designers can compose new robot designs from a database of print-and-fold parts. The designs are tested for the users’ functional specifications via simulation and fabricated on user satisfaction. We present six robots designed and fabricated using a 3D printing based approach, as well as a larger robot cut from sheet metal. We have also conducted a user study that demonstrates that our tool is intuitive for novice designers and expressive enough to create a wide variety of ground robot designs.

Multi-scale assembly with robot teams

In this paper we present algorithms and experiments for multi-scale assembly of complex structures by multi-robot teams. We also focus on tasks where successful completion requires multiple types of assembly operations with a range of precision requirements. We develop a hierarchical planning approach to multi-scale perception in support of multi-scale manipulation, in which the resolution of the perception operation is matched with the required resolution for the manipulation operation. We demonstrate these techniques in the context of a multi-step task where robots assemble large box-like objects, inspired by the assembly of an airplane wing. The robots begin by transporting a wing panel, a coarse manipulation operation that requires a wide field of view, and gradually shifts to a narrower field of view but with more accurate sensors for part alignment and fastener insertion. Within this framework we also provide for failure detection and recovery: upon losing track of a feature, the robots retract to using wider field of view systems to re-localize. Finally, we contribute collaborative manipulation algorithms for assembling complex large objects. First, the team of robots coordinates to transport large assembly parts which are too heavy for a single robot to carry. Second, the fasteners and parts are co-localized for robust insertion and fastening. We implement these ideas using four KUKA youBot robots and present experiments where our robots successfully complete all 80 of the attempted fastener insertion operations.

Interactive robogami: data-driven design for 3D print and fold robots with ground locomotion

The process of designing and programming a new robot requires expert knowledge and design skills that are often acquired over the course of many years. This makes design of new robots difficult for non-experienced users. In addition to design, physical realization of a robot is also time and labor intensive. We propose a new fabrication process for mechanical robots, called 3D print and fold, which combines 3D printing with origami fabrication methods. In our technique, robots are 3D printed as flat faces connected at joints and are then folded into their final shape. To help casual users design ground robots using our 3D print and fold technique, we present our Interactive Robogami system. The system leverages a database of examples created by expert roboticists. A composition tool allows users to create new designs by composing parts from the robots in this database. The system automatically ensures that the assembled robot is fabricable and that it can locomote forward while still giving creative freedom to users.

Functional co-optimization of articulated robots

We present parametric trajectory optimization, a method for simultaneously computing physical parameters, actuation requirements, and robot motions for more efficient robot designs. In this scheme, robot dimensions, masses, and other physical parameters are solved for concurrently with traditional motion planning variables, including dynamically consistent robot states, actuation inputs, and contact forces. Our method requires minimal user domain knowledge, requiring only a coarse guess of the target robot configuration sequence and a parameterized robot topology as input. We demonstrate our results on four simulated robots, one of which we physically fabricated in order to demonstrate physical consistency. We demonstrate that by optimizing robot body parameters alongside robot trajectories, motion planning problems which would otherwise be infeasible can be made feasible, and actuation requirements can be significantly reduced.

Designing cable-driven actuation networks for kinematic chains and trees

In this paper we present an optimization-based approach for the design of cable-driven kinematic chains and trees. Our system takes as input a hierarchical assembly consisting of rigid links jointed together with hinges. The user also specifies a set of target poses or keyframes using inverse kinematics. Our approach places torsional springs at the joints and computes a cable network that allows us to reproduce the specified target poses. We start with a large set of cables that have randomly chosen routing points and we gradually remove the redundancy. Then we refine the routing points taking into account the path between poses or keyframes in order to further reduce the number of cables and minimize required control forces. We propose a reduced coordinate formulation that links control forces to joint angles and routing points, enabling the co-optimization of a cable network together with the required actuation forces. We demonstrate the efficacy of our technique by designing and fabricating a cable-driven, animated character, an animatronic hand, and a specialized gripper.

Building a toolkit for fabricating interactive objects

Despite the recent proliferation of easy-to-use personal fabrication devices, designing custom objects that are useful remains challenging. RFID technology can allow designers to easily embed rich and robust interaction in custom creations at low cost.