An official website of the United States government
Optical communication is of increasing interest as an alternative to acoustic communication for robots operated in underwater environments. Our previous work presented a method for LED-based Simultaneous Localization and Communication (SLAC) that uses the bearing angles, obtained in establishing line-of-sight (LOS) between two beacon nodes and a mobile robot for communication, for geometric triangulation and thus localization of the robot. In this paper, we consider the problem of optical localization in the setting of a network of beacon nodes, and specifically, how to fuse the measurements from multiple pairs of beacon nodes to obtain the target location. A sensitivity metric, which represents how sensitive the target estimate is with respect to the bearing measurement errors, is used for selecting the desired pair of beacon nodes. The proposed solution is evaluated with extensive simulation and preliminary experimentation, in a setting of three beacon nodes and one mobile node. Comparison with an average-based fusion approach and an approach using a fixed pair of beacon nodes demonstrates the efficacy of the proposed approach.
more »
« less
Dynamic Prediction-Based Optical Localization of a Robot During Continuous Movement
Abstract Localization of mobile robots is essential for navigation and data collection. This work presents an optical localization scheme for mobile robots during the robot’s continuous movement, despite that only one bearing angle can be captured at a time. In particular, this paper significantly improves upon our previous works where the robot has to pause its movement in order to acquire the two bearing angle measurements needed for position determination. The latter restriction forces the robot to work in a stop-and-go mode, which constrains the robot’s mobilitty. The proposed scheme exploits the velocity prediction from Kalman filtering, to properly correlate two consecutive measurements of bearing angles with respect to the base nodes (beacons) to produce location measurement. The proposed solution is evaluated in simulation and its advantage is demonstrated through the comparison with the traditional approach where the two consecutive angle measurements are directly used to compute the location.
more »
« less
- Award ID(s):
- 1734272
- PAR ID:
- 10310737
- Date Published:
- Journal Name:
- Proceedings of ASME 2020 Dynamic Systems and Control Conference
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Grab bars have been widely used for assisting elderly people with mobility and providing support for daily activities. This work aims to expand the notion of grab bars beyond fixed installations by the use of a mobile robot that can place a handlebar at any point in space, to optimally support postural transitions. A survey of elderly people and care professionals indicated that such a device must be sturdy, providing secure support without sliding or tipping over, yet also have a compact footprint to be maneuverable within confined spaces. Here, we propose a novel two-body robot structure, consisting of two small-footprint mobile bases connected by a four bar linkage where handlebars are mounted. Each base measures only 29.2 cm wide, making the robot likely the slimmest ever developed for mobile postural assistance. Through kinematic analysis, it is shown that the two-body structure can bear the entire weight of a human body, meeting required load bearing specifications as a handlebar. A control plan is proposed that is generalizable to all robots with two nonholonomic mobile bases connected by a coupling mechanism. This consists of a leader-follower scheme, in which the bases are connected by a virtual spring, as well as various enhancements to waypoint tracking and dead reckoning that allow the robot to smoothly and accurately follow a series of waypoints. A prototype robot is constructed, and its performance is validated experimentally.more » « less
-
Abstract Shape-morphing robots can change their morphology to fulfill different tasks in varying environments, but existing shape-morphing capability is not embedded in a robot’s body, requiring bulky supporting equipment. Here, we report an embedded shape-morphing scheme with the shape actuation, sensing, and locking, all embedded in a robot’s body. We showcase this embedded scheme using three morphing robotic systems: 1) self-sensing shape-morphing grippers that can adapt to objects for adaptive grasping; 2) a quadrupedal robot that can morph its body shape for different terrestrial locomotion modes (walk, crawl, or horizontal climb); 3) an untethered robot that can morph its limbs’ shape for amphibious locomotion. We also create a library of embedded morphing modules to demonstrate the versatile programmable shapes (e.g., torsion, 3D bending, surface morphing, etc.). Our embedded morphing scheme offers a promising avenue for robots to reconfigure their morphology in an embedded manner that can adapt to different environments on demand.more » « less
-
Accurately detecting, localizing, and tracking an unknown and time-varying number of dynamic targets using a team of mobile robots is a challenging problem that requires robots to reason about the uncertainties in their collected measurements. The problem is made more challenging when robots are uncertain about their own states, as this makes it difficult to both collectively localize targets and avoid collisions with one another. In this paper, we introduce the convex uncertain Voronoi (CUV) diagram, a generalization of the standard Voronoi diagram that accounts for the uncertain pose of each individual robot. We then use the CUV diagram to develop distributed multi-target tracking and coverage control algorithms that enable teams of mobile robots to account for bounded uncertainty in the location of each robot. Our algorithms are capable of safely driving mobile robots towards areas of high information distribution while maintaining coverage of the whole area of interest. We demonstrate the efficacy of these algorithms via a series of simulated and hardware tests, and compare the results to our previous work which assumes perfect localization.more » « less
-
The ability of robots to estimate their location is crucial for a wide variety of autonomous operations. In settings where GPS is unavailable, measurements of transmissions from fixed beacons provide an effective means of estimating a robot’s location as it navigates. The accuracy of such a beacon-based localization system depends both on how beacons are distributed in the environment, and how the robot’s location is inferred based on noisy and potentially ambiguous measurements. We propose an approach for making these design decisions automatically and without expert supervision, by explicitly searching for the placement and inference strategies that, together, are optimal for a given environment. Since this search is computationally expensive, our approach encodes beacon placement as a differential neural layer that interfaces with a neural network for inference. This formulation allows us to employ standard techniques for training neural networks to carry out the joint optimization. We evaluate this approach on a variety of environments and settings, and find that it is able to discover designs that enable high localization accuracy.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1115/DSCC2020-3288
