Master’s thesis proposal: computation reuse in stacking and unstacking

Algorithms for dynamic simulation and control are fundamental to many applications, including computer games and movies, medical simulation, and mechanical design. I propose to explore efficient algorithms for finding a stable unstacking sequence -- an order in which we can remove every object from a structure without causing the structure to collapse under gravity at any step. We begin with a basic unstacking sequence algorithm: consider the set of all objects in a structure. Collect all possible subsets into a disassembly graph. Search the graph, testing the stability of each node as it is visited. Any path of stable nodes from start to goal is a stable unstacking sequence. I propose to show how we can improve the performance of individual stability tests for three-dimensional structures with Coulomb friction, and give effective methods for searching the disassembly graph. I will also analyze the computational complexity of stable unstacking problems, and explore a classification of structures based on characteristics of their stable unstacking sequences. In preliminary work, I have shown that we can reuse computation from one stability test of a planar subassembly to the next. The implementation, which solves the system dynamics as a linear complementarity problem (LCP), outperforms an implementation that solves the system statics as a linear program (LP). This is surprising because LCPs are more complex than LPs, and dynamics equations are more complex than statics equations

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

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

Automated re-prefabrication system for buildings using robotics

Prefabrication has the advantages of simplicity, speed and economy but has been inflexible to changes in design which is a primary reason behind its limited market share in the construction industry. To tackle this drawback, this study presents a Robotic Prefabrication System (RPS) which employs a new concept called “re-fabrication”: the automatic disassembly of a prefabricated structure and its reconstruction according to a new design. The RPS consists of a software module and a hardware module. First, the software employs the 3D model of a prefabricated structure as input, and returns motor control command output to the hardware. There are two underlying algorithms developed in the software module. First, a novel algorithm automatically compares the old and new models and identifies the components which the two models do not have in common in order to enable disassembly of the original structure and its refabrication into the new design. In addition, an additional novel algorithm computes the optimal refabrication sequence to transform one model into another according to the differences identified. Meanwhile, the hardware module takes the motor control commands as input and executes the appropriate assembly/disassembly operations, and returns the desired refabricated structure in realtime. Validation tests on two lab-scaled prefabricated structures demonstrate that the system successfully generated the desired refabrication sequences and performed all assembly operations with acceptable placement precision