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This research investigates different visual features for augmented reality (AR)–based assembly instructions. Since the beginning of AR research, one of its most popular application areas has been manual assembly assistance. A typical AR assembly application indicates the necessary manual assembly operations by generating visual representations of parts that are spatially registered with, and superimposed on, a video representation of the physical product to be assembled. Research in this area indicates the advantages of this type of assembly instruction presentation. This research investigates different types of visual features for different assembly operations. The hypothesis is that in order to gain an advantage from AR, the visual features used to explain a particular assembly operation must correspond to its relative difficulty level. The final goal is to associate different types of visual features to different levels of task complexity. A user study has been conducted in order to compare different visual features at different operation complexity levels. The results support the hypothesis.

The task of locating a source based on the measurements of the signal emitted/emanating from it is called the source-seeking problem. In the past few years, there has been a lot of interest in deploying autonomous platforms for source-seeking. Some of the challenging issues with implementing autonomous source-seeking are the lack of a priori knowledge about the distribution of the emitted signal and presence of noise in both the environment and on-board sensor measurements. This paper proposes a planner for a swarm of robots engaged in seeking an electromagnetic source. The navigation strategy for the planner is based on Particle Swarm Optimization (PSO) which is a population-based stochastic optimization technique. An equivalence is established between particles generated in the traditional PSO technique, and the mobile agents in the swarm. Since the positions of the robots are updated using the PSO algorithm, modifications are required to implement the PSO algorithm on real robots to incorporate collision avoidance strategies. The modifications necessary to implement PSO on mobile robots, and strategies to adapt to real environments are presented in this paper. Our results are also validated on an experimental testbed. Note to Practitioners-This paper is inspired by the source seeking problem in which the signal emitted from the source is assumed to be very noisy, and the spatial distribution is assumed to be non-smooth. We focus our work specifically on electromagnetic sources. However, the strategies proposed in this paper are also applicable to other kinds of sources, for example, nuclear, radiological, chemical or biological. We develop a planner for a swarm of mobile agents that try to locate an unknown electromagnetic source. The mobile agents know their own positions and can measure the signal strength at their current location. They can share information among themselves, and plan for the next step. We propose a complete solution to ensure the effectiveness of PSO in complex environments where collisions may occur. We incorporate static and dynamic obstacle avoidance strategies in PSO to make it fully applicable to real-world scenario. We validate the proposed technique on an experimental testbed. As a part of our future work, we will extend the technique to locate multiple sources of different kinds.

Recently proposed binary defocusing techniques have led to ultrafast speed 3D shape measurement, but they are generally limited to measurement of a single object at a time. Introducing additional gray coded patterns for point-by-point phase unwrapping could permit simultaneous multiple-object measurement. However, when the objects are moving rapidly, the displacement between the first captured pattern and the last can be significant, and pose challenges related to the precisely designed gray codes. This paper presents a new phase unwrapping strategy that combines the conventional spatial phase unwrapping with the gray code to resolve motion related phase unwrapping problems. A system with a speed of 5,000 Hz was developed to verify the performance of the proposed technique.