Tool Exchangeable Grasp/Assembly Planner

This paper proposes a novel assembly planner for a manipulator which can simultaneously plan assembly sequence, robot motion, grasping configuration, and exchange of grippers. Our assembly planner assumes multiple grippers and can automatically selects a feasible one to assemble a part. For a given AND/OR graph of an assembly task, we consider generating the assembly graph from which assembly motion of a robot can be planned. The edges of the assembly graph are composed of three kinds of paths, i.e., transfer/assembly paths, transit paths and tool exchange paths. In this paper, we first explain the proposed method for planning assembly motion sequence including the function of gripper exchange. Finally, the effectiveness of the proposed method is confirmed through some numerical examples and a physical experiment.Comment: This is to appear Int. Conf. on Intelligent Autonomous System

Optimization of Robot Motion Planning using Ant Colony Optimization

Motion planning in robotics is a process to compute a collision free path between the initial and final configuration among obstacles. To plan a collision free path in the workspace, it would need to plan the motion of every point of its shaping according its degree of freedom. The motion of robot between obstacles is represented by a path in configuration space. It is an imaginary concept. Motion planning is aimed at enabling robots with capabilities of automatically deciding and executing a sequence motion in order to achieve a task without ollision with other objects in a given environment. Motion planning in a robot workspace for robotic assembly depends on sequence of parts or the order they are arranged to produce a robotic assembly product obeying all the constraints and instability of base assembly movement. If the number of parts increases the sequencing becomes difficult and hence the path planning. As multiple no. of paths are possible, the path is considered to be optimal when it minimizes the travelling time while satisfying the process constraint. For this purpose, it is necessary to select appropriate optimization technique for optimization of paths. Such types of problem can be solved by metaheuristic methods.The present work utilizes ACO for the generation of optimal motion planning sequence. The present algorithm is based on ant's behavior, pheromone update & pheromone evaporation and is used to enhance the local search. This procedure is applied to a grinder assembly, driver assembly and car alternator assembly. Two robots like adept-one and puma-762 are selected for picking and placing operation of parts in their workspace

Composing Diverse Policies for Temporally Extended Tasks

Robot control policies for temporally extended and sequenced tasks are often characterized by discontinuous switches between different local dynamics. These change-points are often exploited in hierarchical motion planning to build approximate models and to facilitate the design of local, region-specific controllers. However, it becomes combinatorially challenging to implement such a pipeline for complex temporally extended tasks, especially when the sub-controllers work on different information streams, time scales and action spaces. In this paper, we introduce a method that can compose diverse policies comprising motion planning trajectories, dynamic motion primitives and neural network controllers. We introduce a global goal scoring estimator that uses local, per-motion primitive dynamics models and corresponding activation state-space sets to sequence diverse policies in a locally optimal fashion. We use expert demonstrations to convert what is typically viewed as a gradient-based learning process into a planning process without explicitly specifying pre- and post-conditions. We first illustrate the proposed framework using an MDP benchmark to showcase robustness to action and model dynamics mismatch, and then with a particularly complex physical gear assembly task, solved on a PR2 robot. We show that the proposed approach successfully discovers the optimal sequence of controllers and solves both tasks efficiently.Comment: arXiv admin note: substantial text overlap with arXiv:1906.1009

Semi-automatic Design for Disassembly Strategy Planning: An Augmented Reality Approach

Abstract The mounting attention to environmental issues requires adopting better disassembly procedures at the product's End of Life. Planning and reckoning different disassembly strategies in the early stage of the design process can improve the development of sustainable products with an easy dismissing and recycling oriented approach. Nowadays many Computer Aided Process Planning software packages provide optimized assembly or disassembly sequences, but they are mainly based on a time and cost compression approach, neglecting the human factor. The environment we developed is based upon the integration of a CAD, an Augmented Reality tool, a Leap Motion Controller device, see-through glasses and an algorithm for disassembly strategies evaluation: this approach guarantees a more effective interaction with the 3D real and virtual assembly than an approach relying only on a CAD based disassembly sequence planning. In such a way, the operator may not test in a more natural and intuitive way automatic disassembly sequences, but he/she can also propose different strategies to improve the ergonomics. The methodology has been tested in a real case study to evaluate the strength points and criticalities of this approach

Motion Planning for Relocatable Robots Performing On-Orbit Locomotion and Manipulation Tasks

In-space assembly is a key technology for the future development of large infrastructures in space, from space stations and telescopes, to solar power plants or planetary bases. Such structures are much larger than cargo areas in current launchers, therefore they must be sent in separate pieces that are assembled in situ, typically using relocatable robotic manipulators. The efficient exploitation of the locomotion and manipulation (loco-manipulation) abilities for such robotic systems requires suitable planning tools. In this paper, we present a motion planning approach for exploiting loco-manipulation abilities of self-relocatable space robots, assuming that they move over specific interconnects that provide the required mechanical, power and data connectivity. The proposed approach consists of three planning layers: a high-level planning for obtaining the contact sequence, a low-level planning for the joint trajectories, and a validation layer. The motion planner provides plans for single locomotion and manipulation tasks, as well as combined loco-manipulation tasks. The approach is illustrated with examples for two robotic systems: MOSAR-WM, a relocatable walking manipulator, and a multi-arm robot (MAR) equipped with two arms attached to a central tors

Automated sequence and motion planning for robotic spatial extrusion of 3D trusses

While robotic spatial extrusion has demonstrated a new and efficient means to fabricate 3D truss structures in architectural scale, a major challenge remains in automatically planning extrusion sequence and robotic motion for trusses with unconstrained topologies. This paper presents the first attempt in the field to rigorously formulate the extrusion sequence and motion planning (SAMP) problem, using a CSP encoding. Furthermore, this research proposes a new hierarchical planning framework to solve the extrusion SAMP problems that usually have a long planning horizon and 3D configuration complexity. By decoupling sequence and motion planning, the planning framework is able to efficiently solve the extrusion sequence, end-effector poses, joint configurations, and transition trajectories for spatial trusses with nonstandard topologies. This paper also presents the first detailed computation data to reveal the runtime bottleneck on solving SAMP problems, which provides insight and comparing baseline for future algorithmic development. Together with the algorithmic results, this paper also presents an open-source and modularized software implementation called Choreo that is machine-agnostic. To demonstrate the power of this algorithmic framework, three case studies, including real fabrication and simulation results, are presented.Comment: 24 pages, 16 figure

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

Automated design analysis, assembly planning and motion study analysis using immersive virtual reality

Previous research work at Heriot-Watt University using immersive virtual reality (VR) for cable harness design showed that VR provided substantial productivity gains over traditional computer-aided design (CAD) systems. This follow-on work was aimed at understanding the degree to which aspects of this technology were contributed to these benefits and to determine if engineering design and planning processes could be analysed in detail by nonintrusively monitoring and logging engineering tasks. This involved using a CAD-equivalent VR system for cable harness routing design, harness assembly and installation planning that can be functionally evaluated using a set of creative design-tasks to measure the system and users' performance. A novel design task categorisation scheme was created and formalised which broke down the cable harness design process and associated activities. The system was also used to demonstrate the automatic generation of usable bulkhead connector, cable harness assembly and cable harness installation plans from non-intrusive user logging. Finally, the data generated from the user-logging allowed the automated activity categorisation of the user actions, automated generation of process flow diagrams and chronocyclegraphs