Predicting Energy Consumption of Ground Robots On Uneven Terrains

Optimizing energy consumption for robot navigation in fields requires energy-cost maps. However, obtaining such a map is still challenging, especially for large, uneven terrains. Physics-based energy models work for uniform, flat surfaces but do not generalize well to these terrains. Furthermore, slopes make the energy consumption at every location directional and add to the complexity of data collection and energy prediction. In this paper, we address these challenges in a data-driven manner. We consider a function which takes terrain geometry and robot motion direction as input and outputs expected energy consumption. The function is represented as a ResNet-based neural network whose parameters are learned from field-collected data. The prediction accuracy of our method is within 12% of the ground truth in our test environments that are unseen during training. We compare our method to a baseline method in the literature: a method using a basic physics-based model. We demonstrate that our method significantly outperforms it by more than 10% measured by the prediction error. More importantly, our method generalizes better when applied to test data from new environments with various slope angles and navigation directions

HEROES: Unreal Engine-based Human and Emergency Robot Operation Education System

Training and preparing first responders and humanitarian robots for Mass Casualty Incidents (MCIs) often poses a challenge owing to the lack of realistic and easily accessible test facilities. While such facilities can offer realistic scenarios post an MCI that can serve training and educational purposes for first responders and humanitarian robots, they are often hard to access owing to logistical constraints. To overcome this challenge, we present HEROES- a versatile Unreal Engine simulator for designing novel training simulations for humans and emergency robots for such urban search and rescue operations. The proposed HEROES simulator is capable of generating synthetic datasets for machine learning pipelines that are used for training robot navigation. This work addresses the necessity for a comprehensive training platform in the robotics community, ensuring pragmatic and efficient preparation for real-world emergency scenarios. The strengths of our simulator lie in its adaptability, scalability, and ability to facilitate collaboration between robot developers and first responders, fostering synergy in developing effective strategies for search and rescue operations in MCIs. We conducted a preliminary user study with an 81% positive response supporting the ability of HEROES to generate sufficiently varied environments, and a 78% positive response affirming the usefulness of the simulation environment of HEROES

Risk-aware Path and Motion Planning for a Tethered Aerial Visual Assistant in Unstructured or Confined Environments

This research aims at developing path and motion planning algorithms for a tethered Unmanned Aerial Vehicle (UAV) to visually assist a teleoperated primary robot in unstructured or confined environments. The emerging state of the practice for nuclear operations, bomb squad, disaster robots, and other domains with novel tasks or highly occluded environments is to use two robots, a primary and a secondary that acts as a visual assistant to overcome the perceptual limitations of the sensors by providing an external viewpoint. However, the benefits of using an assistant have been limited for at least three reasons: (1) users tend to choose suboptimal viewpoints, (2) only ground robot assistants are considered, ignoring the rapid evolution of small unmanned aerial systems for indoor flying, (3) introducing a whole crew for the second teleoperated robot is not cost effective, may introduce further teamwork demands, and therefore could lead to miscommunication. This dissertation proposes to use an autonomous tethered aerial visual assistant to replace the secondary robot and its operating crew. Along with a pre-established theory of viewpoint quality based on affordances, this dissertation aims at defining and representing robot motion risk in unstructured or confined environments. Based on those theories, a novel high level path planning algorithm is developed to enable risk-aware planning, which balances the tradeoff between viewpoint quality and motion risk in order to provide safe and trustworthy visual assistance flight. The planned flight trajectory is then realized on a tethered UAV platform. The perception and actuation are tailored to fit the tethered agent in the form of a low level motion suite, including a novel tether-based localization model with negligible computational overhead, motion primitives for the tethered airframe based on position and velocity control, and two differentComment: Ph.D Dissertatio

Risk-aware Path and Motion Planning for a Tethered Aerial Visual Assistant in Unstructured or Confined Environments

This research aims at developing path and motion planning algorithms for a tethered Unmanned Aerial Vehicle (UAV) to visually assist a teleoperated primary robot in unstructured or confined environments. The emerging state of the practice for nuclear operations, bomb squad, disaster robots, and other domains with novel tasks or highly occluded environments is to use two robots, a primary and a secondary that acts as a visual assistant to overcome the perceptual limitations of the sensors by providing an external viewpoint. However, the benefits of using an assistant have been limited for at least three reasons: (1) users tend to choose suboptimal viewpoints, (2) only ground robot assistants are considered, ignoring the rapid evolution of small unmanned aerial systems for indoor flying, (3) introducing a whole crew for the second teleoperated robot is not cost effective, may introduce further teamwork demands, and therefore could lead to miscommunication. This dissertation proposes to use an autonomous tethered aerial visual assistant to replace the secondary robot and its operating crew. Along with a pre-established theory of viewpoint quality based on affordances, this dissertation aims at defining and representing robot motion risk in unstructured or confined environments. Based on those theories, a novel high level path planning algorithm is developed to enable risk-aware planning, which balances the tradeoff between viewpoint quality and motion risk in order to provide safe and trustworthy visual assistance flight. The planned flight trajectory is then realized on a tethered UAV platform. The perception and actuation are tailored to fit the tethered agent in the form of a low level motion suite, including a novel tether-based localization model with negligible computational overhead, motion primitives for the tethered airframe based on position and velocity control, and two different approaches to negotiate tether with complex obstacle-occupied environments. The proposed research provides a formal reasoning of motion risk in unstructured or confined spaces, contributes to the field of risk-aware planning with a versatile planner, and opens up a new regime of indoor UAV navigation: tethered indoor flight to ensure battery duration and failsafe in case of vehicle malfunction. It is expected to increase teleoperation productivity and reduce costly errors in scenarios such as safe decommissioning and nuclear operations in the Fukushima Daiichi facility

Space station systems: A bibliography with indexes

This bibliography lists 967 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1, 1987 and June 30, 1987. Its purpose is to provide helpful information to the researcher, manager, and designer in technology development and mission design according to system, interactive analysis and design, structural and thermal analysis and design, structural concepts and control systems, electronics, advanced materials, assembly concepts, propulsion, and solar power satellite systems. The coverage includes documents that define major systems and subsystems, servicing and support requirements, procedures and operations, and missions for the current and future space station

Estimating Achievable Range of Ground Robots Operating on Single Battery Discharge for Operational Efficacy Amelioration

Mobile robots are increasingly being used to assist with active pursuit and law enforcement. One major limitation for such missions is the resource (battery) allocated to the robot. Factors like nature and agility of evader, terrain over which pursuit is being carried out, plausible traversal velocity and the amount of necessary data to be collected all influence how long the robot can last in the field and how far it can travel. In this paper, we develop an analytical model that analyzes the energy utilization for a variety of components mounted on a robot to estimate the maximum operational range achievable by the robot operating on a single battery discharge. We categorize the major consumers of energy as: 1.) ancillary robotic functions such as computation, communication, sensing etc., and 2.) maneuvering which involves propulsion, steering etc. Both these consumers draw power from the common power source but the achievable range is largely affected by the proportion of power available for maneuvering. For this case study, we performed experiments with real robots on planar and graded surfaces and evaluated the estimation error for each case.Peer reviewe

Algorithm and design improvements for indirect time of flight range imaging cameras

This thesis describes the development of a compact and modularised indirect time of flight range imaging camera. These cameras commonly use the Amplitude Modulated Continuous Wave (AMCW) technique. For this technique, an entire scene is illuminated with light modulated at a high frequency. An image sensor is also modulated and the phase shift introduced between the two modulation signals, due to the transit time of the light reflecting off objects in the scene and returning to the camera, is used to measure the distance. The system constructed for this thesis is controlled by a Cyclone III FPGA and is capable of producing full field of view range images in real time with no additional computational resources. A PMD19K-2 sensor is used as the modulatable image sensor, and is capable of modulation frequencies up to 40 MHz. One significant issue identified with this range imaging technology is that the precision of the range measurements are often dependent on the properties of the object being measured. The dynamic range of the camera is therefore very important when imaging high contrast scenes. Variable Frame Rate Imaging is a novel technique that is developed as part of this thesis and is shown to have promise for addressing this issue. Traditional theory for indirect time of flight cameras is expanded to describe this technique and is experimentally verified. A comparison is made between this technique and traditional High Dynamic Range Imaging. Furthermore, this technique is extended to provide a constant precision measurement of a scene, regardless of the properties of the objects in the scene. It is shown that the replacement of the standard phase detection algorithm with a different algorithm can both reduce the linearity error in the phase measurements caused by harmonics in the correlation waveform and ameliorate axial motion error caused by relative motion of the camera and the object being measured. The new algorithm requires a trivial increase in computational power over the standard algorithm and can be implemented without any significant changes to the standard hardware used in indirect time of flight cameras. Finally, the complete system is evaluated in a number of real world scenarios. Applications in both 3D modelling and mobile robotics are demonstrated and tests are performed for a variety of scenarios including dynamic scenes using a Pioneer 2 robot

Cage row arrangement affects the performance of laying hens in the hot humid tropics

Although the traditional cage system of housing laying hens is gradually being faced out due to welfare reasons, cages are still common in most developing tropical countries in different arrangements. In a 12-week experiment, the effects of a three cage row arrangement on hen-day production and egg qualities of Shaver Brown hens was studied. Data were collected from 2 layer sheds housing 9,000 hens in a 3-cage row arrangement (southern row, northern row and middle row) with 3,000 hens per row. Data were analysed for a randomized complete block design where cage rows were the treatments and weeks the blocks. Results showed no significant effects of cage row arrangement on feed intake, hen-day production, per cent yolk and Haugh unit (P>0.05). Egg weight, egg mass and per cent shell were significantly reduced and feed conversion ratio increased on the middle row (P<0.05). Egg weight, egg mass, per cent shell and feed conversion ratio did not differ between the side rows (P>0.05). These results suggest that battery cage row arrangement may not affect the rate of lay but egg weight, egg mass and efficiency of feed utilisation may be adversely affected in hens housed in the middle row. These findings have both economic and welfare implications

Medical Robotics

The first generation of surgical robots are already being installed in a number of operating rooms around the world. Robotics is being introduced to medicine because it allows for unprecedented control and precision of surgical instruments in minimally invasive procedures. So far, robots have been used to position an endoscope, perform gallbladder surgery and correct gastroesophogeal reflux and heartburn. The ultimate goal of the robotic surgery field is to design a robot that can be used to perform closed-chest, beating-heart surgery. The use of robotics in surgery will expand over the next decades without any doubt. Minimally Invasive Surgery (MIS) is a revolutionary approach in surgery. In MIS, the operation is performed with instruments and viewing equipment inserted into the body through small incisions created by the surgeon, in contrast to open surgery with large incisions. This minimizes surgical trauma and damage to healthy tissue, resulting in shorter patient recovery time. The aim of this book is to provide an overview of the state-of-art, to present new ideas, original results and practical experiences in this expanding area. Nevertheless, many chapters in the book concern advanced research on this growing area. The book provides critical analysis of clinical trials, assessment of the benefits and risks of the application of these technologies. This book is certainly a small sample of the research activity on Medical Robotics going on around the globe as you read it, but it surely covers a good deal of what has been done in the field recently, and as such it works as a valuable source for researchers interested in the involved subjects, whether they are currently “medical roboticists” or not