Lightweight means of actuation for use in space-based robotics applications

In the field of robotics many researchers have devoted a large amount of time to pursuing means to reduce the weight of robotic systems. For space robotics, this becomes even more important due to launch cost being directly affected by weight. During review, potential progress involving weight reduction of actuators has been encountered, which it is necessary to investigate further in order to ascertain the potential advantages and disadvantages of such work. The contribution to be put forth here is a review of means by which reductions in weight can be achieved, with particular emphasis on space robotic actuation sub-systems. Ideas will be posited about the possible configurations which could be explored to reduce weight whilst attempting to maintain performance. It is expected that this contribution will provide evidence-based support for some future research directions, and will also help to stimulate discussion and further work on the subject of lightweight robotics and lightweight actuators. The next stages of this project aim to enhance some of the actuation ideas investigated so far, test these comparatively against one another, and critically review them alongside existing lightweight actuation methods. Following this, simulation of actuation concepts being applied to robotic applications will take place. This is in order to evaluate their performance in microgravity environments and to test their versatility. This process, as part of this project, will also be discussed in this pape

The design of a robotic arm link using functionally graded materials : a case study

The development and design of a functionally-graded material (FGM) robotic arm for supporting and manipulating a vision system is discussed in this paper. The aim is to understand if using FGMs effectively reduce mass compared to single material parts. The evolution of ideas using topological optimisation (TO) and FGMs towards the design are shown and reviewed. The final design uses TO, and as such needs to be manufactured using additive manufacture (AM). Constraints have been put in place to ensure physical manufacturability is possible. The final design reduces the mass compared to the original arm by 61.4%

A methodology for design of lightweight robotic arm links in harsh environments

A methodology for the creation of functionally graded material (FGM) parts in harsh environments has been developed. It uses a two-stage optimisation approach that focusses first on the task-dependent material choice and then on the topological optimisation (TO) of the part. Constraints are in place to ensure the part can be manufactured, including the extent/smoothness of material blending and the minimum feature size and layer thickness. Thought is also put into space-specific concerns, such as radiation and cyclic thermal heating. The methodology assumes an initial design solution has already been generated, and covers from the beginning of the CAD phase to the end of the computational testing phase. Design constraints are created with additive manufacture (AM) in mind, and suggestions are made for material mixing processes for FGM, material layout strategies and manufacturability, including scanning strategies and surface finish

Autonomous navigation with ROS for a mobile robot in agricultural fields

Autonomous monitoring of agricultural farms and fields has recently become feasible due to continuing advances in robotics technology, but many notable challenges remain. In this paper, we describe the state of ongoing work to create a fully autonomous ground rover platform for monitoring and intervention tasks on modern farms that is built using inexpensive and off the shelf hardware and Robot Operating System (ROS) software so as to be affordable to farmers. The hardware and software architectures used in this rover are described along with challenges and solutions in odometry and localization, object recognition and mapping, and path planning algorithms under the constraints of the current hardware. Results obtained from laboratory and field testing show both the key challenges to be overcome, and the current successes in applying a low-cost rover platform to the task of autonomously navigating the outdoor farming environment

A novel haptic model and environment for maxillofacial surgical operation planning and manipulation

This paper presents a practical method and a new haptic model to support manipulations of bones and their segments during the planning of a surgical operation in a virtual environment using a haptic interface. To perform an effective dental surgery it is important to have all the operation related information of the patient available beforehand in order to plan the operation and avoid any complications. A haptic interface with a virtual and accurate patient model to support the planning of bone cuts is therefore critical, useful and necessary for the surgeons. The system proposed uses DICOM images taken from a digital tomography scanner and creates a mesh model of the filtered skull, from which the jaw bone can be isolated for further use. A novel solution for cutting the bones has been developed and it uses the haptic tool to determine and define the bone-cutting plane in the bone, and this new approach creates three new meshes of the original model. Using this approach the computational power is optimized and a real time feedback can be achieved during all bone manipulations. During the movement of the mesh cutting, a novel friction profile is predefined in the haptical system to simulate the force feedback feel of different densities in the bone

Visual pose estimation system for autonomous rendezvous of spacecraft

In this work, a tracker spacecraft equipped with a short-range vision system is tasked with visually identifying a target spacecraft and determining its relative angular velocity and relative linear velocity using only visual information from onboard cameras. Focusing on methods that are feasible for implementation on relatively simple spacecraft hardware, we locate and track objects in three-dimensional space using conventional high-resolution cameras, saving cost and power compared to laser or infrared ranging systems. Identification of the target is done by means of visual feature detection and tracking across rapid, successive frames, taking the perspective matrix of the camera system into account, and building feature maps in three dimensions over time. Features detected in two-dimensional images are matched and triangulated to provide three-dimensional feature maps using structure-from-motion techniques. This methodology allows one, two, or more cameras with known baselines to be used for triangulation, with more images resulting in higher accuracy. Triangulated points are organized by means of orientation histogram descriptors and used to identify and track parts of the target spacecraft over time. This allows some estimation of the target spacecraft's motion even if parts of the spacecraft are obscured or in shadow. The state variables with respect to the camera system are extracted as a relative rotation quaternion and relative translation vector for the target. Robust tracking of the state variables for the target spacecraft is accomplished by an embedded adaptive unscented Kalman filter. In addition to estimation of the target quaternion from visual Information, the adaptive filter can also identify when tracking errors have occurred by measurement of the residual. Significant variations in lighting can be tolerated as long as the movement of the satellite is consistent with the system model, and illumination changes slowly enough for state variables to be estimated periodically. Inertial measurements over short periods of time can then be used to determine the movement of both the tracker and target spacecraft. In addition, with a sufficient number of features tracked, the center of mass of the target can be located. This method is tested using laboratory images of spacecraft movement with a simulated spacecraft movement model. Varying conditions are applied to demonstrate the effectiveness and limitations of the system for online estimation of the movement of a target spacecraft at close range

An engineering design tool capable of nurturing the development of new mechatronic actuators

This paper will cover use of a component selection tool in understanding and forecasting the actuation needs of robotic systems in the future. As part of an ongoing work, a component selection tool to assist mechatronics engineers has been developed. Pursuant to the conference's theme, this paper will focus on how effective the tool is in nurturing innovation of new actuation components and systems. Discussion will take place covering topics such as: development and intended primary and secondary applications of the component selection tool; applying the tool to component selection; how the tool can be used to identify ideal requirements in a design process; how the tool can be used to generate solutions which attempt to encompass what is required of an ideal solution; how the tool is relevant to mechatronics presently; and, how ongoing use could affect a paradigmatic shift in the field of mechatronic systems design and configuration

Target shape identification for nanosatellites using monocular point cloud techniques

Many mission scenarios for nanosatellites and CubeSat hardware have already been created that will require autonomous target tracking and rendezvous maneuvers in close proximity to other orbiting objects. While many existing hardware and software designs require the use of rangefinders or laser-based sensors to identify and track nearby objects, the size and power limitations of a CubeSat make a simple monocular system greatly preferable, so long as reliable identification can still be carried out. This presentation details the development and testing of an embedded algorithm for visually identifying the shape of a target and tracking its movement over time, which can include rotation about any axis. A known three-dimensional geometric model is required for use as a reference when identifying a target. First, feature descriptors implemented in the OpenCV framework are used to create a sparse point cloud of features from a nearby object. Using structure-from-motion (SfM) methods, feature points obtained over successive images can be triangulated in three dimensions to obtain a pose estimate. Statistical shape recognition is then used to identify the object based on features from available three-dimensional models. While more feature points make the identification more accurate, more computing power is required, and within the limitations of an embedded system, the balance of speed and accuracy is evaluated. The algorithm is designed to be efficient enough for feasible operation using embedded hardware useable on a CubeSat, and can be used with appropriate hardware for real-time operation. An overview of the algorithm and vision system design is given, and some initial test results for a simulated orbital rendezvous scenario are provided for some indication of the performance of these methods. Applications of interest for this type of algorithm include external monitoring of other spacecraft, robotic capture and docking, and space debris removal