Avian-Inspired Claws Enable Robot Perching or Walking

Multimodal UAVs (Unmanned Aerial Vehicles) are rarely capable of more than two modalities, i.e., flying and walking or flying and perching. However, being able to fly, perch, and walk could further improve their usefulness by expanding their operating envelope. For instance, an aerial robot could fly a long distance, perch in a high place to survey the surroundings, then walk to avoid obstacles that could potentially inhibit flight. Birds are capable of these three tasks, and so offer a practical example of how a robot might be developed to do the same. In this paper, we present a specialized avian-inspired claw design to enable UAVs to perch passively or walk. The key innovation is the combination of a Hoberman linkage leg with Fin Ray claw that uses the weight of the UAV to wrap the claw around a perch, or hyperextend it in the opposite direction to form a curved-up shape for stable terrestrial locomotion. Because the design uses the weight of the vehicle, the underactuated design is lightweight and low power. With the inclusion of talons, the 45g claws are capable of holding a 700g UAV to an almost 20-degree angle on a perch. In scenarios where cluttered environments impede flight and long mission times are required, such a combination of flying, perching, and walking is critical.Comment: 15 pages, 12 figure

Tactile Perception And Visuotactile Integration For Robotic Exploration

As the close perceptual sibling of vision, the sense of touch has historically received less than deserved attention in both human psychology and robotics. In robotics, this may be attributed to at least two reasons. First, it suffers from the vicious cycle of immature sensor technology, which causes industry demand to be low, and then there is even less incentive to make existing sensors in research labs easy to manufacture and marketable. Second, the situation stems from a fear of making contact with the environment, avoided in every way so that visually perceived states do not change before a carefully estimated and ballistically executed physical interaction. Fortunately, the latter viewpoint is starting to change. Work in interactive perception and contact-rich manipulation are on the rise. Good reasons are steering the manipulation and locomotion communities’ attention towards deliberate physical interaction with the environment prior to, during, and after a task. We approach the problem of perception prior to manipulation, using the sense of touch, for the purpose of understanding the surroundings of an autonomous robot. The overwhelming majority of work in perception for manipulation is based on vision. While vision is a fast and global modality, it is insufficient as the sole modality, especially in environments where the ambient light or the objects therein do not lend themselves to vision, such as in darkness, smoky or dusty rooms in search and rescue, underwater, transparent and reflective objects, and retrieving items inside a bag. Even in normal lighting conditions, during a manipulation task, the target object and fingers are usually occluded from view by the gripper. Moreover, vision-based grasp planners, typically trained in simulation, often make errors that cannot be foreseen until contact. As a step towards addressing these problems, we present first a global shape-based feature descriptor for object recognition using non-prehensile tactile probing alone. Then, we investigate in making the tactile modality, local and slow by nature, more efficient for the task by predicting the most cost-effective moves using active exploration. To combine the local and physical advantages of touch and the fast and global advantages of vision, we propose and evaluate a learning-based method for visuotactile integration for grasping

Recent Advances in Multi Robot Systems

To design a team of robots which is able to perform given tasks is a great concern of many members of robotics community. There are many problems left to be solved in order to have the fully functional robot team. Robotics community is trying hard to solve such problems (navigation, task allocation, communication, adaptation, control, ...). This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. It is focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. The book consists of 16 chapters introducing both basic research and advanced developments. Topics covered include kinematics, dynamic analysis, accuracy, optimization design, modelling, simulation and control of multi robot systems

Increasing the Automation Level of Serial Robotic Manipulators with Optimal Design and Collision-free Path Control

The current hydraulic robotic manipulator mechanisms for heavy-duty machines are a mature technology, and their kinematics has been developed with a focus on the human operator maneuvering a hydraulically controlled system without numerical control input. As the trend in heavy-duty manipulators is increased automation, computer control systems are increasingly being widely used, and the requirements for robotic manipulator kinematics are different. Computer control enables a different kind of robotic manipulator kinematics, which is not optimum for direct control by a human operator, because the joint motions related to the different trajectories are not native for the human mind. Numerically controlled robotic manipulators can accept kinematics that is more efficient at doing the job expected by the customer.To increase the autonomous level of robotic manipulator, the optimal structure is not enough, but it is a part of the solution toward a fully autonomous manipulator. The control system of the manipulator is the main part of computer-controlled manipulators. A collision avoidance system plays an important role in the field of autonomous robotics. Without collision avoidance functionality, it is quite obvious that only very simple movements and tasks can be carried out automatically. With more complicated movement and manipulators, some kind of collision avoidance system is required. An unknown or changing environment increases the need for an intelligent collision avoidance system that can find a collision-free path in a dynamic environment.This thesis deals with these fundamental challenges by optimizing the serial manipulator structure for the desired task and proposing a collision avoidance control system. The basic requirement in the design of such a robotic manipulator is to make sure that all the desired task points can be achieved without singularities. These properties are difficult to achieve with the general shape and type of robotic manipulators. In this research work, a task-based kinematic synthesis approach with the proper optimization method ensures that the desired requirements can be fulfilled.To enable autonomous task execution for robotic manipulators, the control systems must have a collision avoidance system that can prevent different kinds of collisions. These collisions include self-collisions, collisions with other manipulators, collisions with obstacles, and collisions with the environment. Furthermore, there can be multiple simultaneous possible collisions that need to prevented, and the collision system must be able to handle all these collisions in real-time. In this research work, a real-time collision avoidance control approach is proposed to handle these issues. Overall, both topics, covered in this thesis, are believed to be key elements for increasing the automation of serial robotic manipulators

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

Advances in Intelligent Robotics and Collaborative Automation

This book provides an overview of a series of advanced research lines in robotics as well as of design and development methodologies for intelligent robots and their intelligent components. It represents a selection of extended versions of the best papers presented at the Seventh IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications IDAACS 2013 that were related to these topics. Its contents integrate state of the art computational intelligence based techniques for automatic robot control to novel distributed sensing and data integration methodologies that can be applied to intelligent robotics and automation systems. The objective of the text was to provide an overview of some of the problems in the field of robotic systems and intelligent automation and the approaches and techniques that relevant research groups within this area are employing to try to solve them.The contributions of the different authors have been grouped into four main sections:• Robots• Control and Intelligence• Sensing• Collaborative automationThe chapters have been structured to provide an easy to follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications

Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space 1994

The Third International Symposium on Artificial Intelligence, Robotics, and Automation for Space (i-SAIRAS 94), held October 18-20, 1994, in Pasadena, California, was jointly sponsored by NASA, ESA, and Japan's National Space Development Agency, and was hosted by the Jet Propulsion Laboratory (JPL) of the California Institute of Technology. i-SAIRAS 94 featured presentations covering a variety of technical and programmatic topics, ranging from underlying basic technology to specific applications of artificial intelligence and robotics to space missions. i-SAIRAS 94 featured a special workshop on planning and scheduling and provided scientists, engineers, and managers with the opportunity to exchange theoretical ideas, practical results, and program plans in such areas as space mission control, space vehicle processing, data analysis, autonomous spacecraft, space robots and rovers, satellite servicing, and intelligent instruments

A study of mobile robot motion planning

This thesis studies motion planning for mobile robots in various environments. The basic tools for the research are the configuration space and the visibility graph. A new approach is developed which generates a smoothed minimum time path. The difference between this and the Minimum Time Path at Visibility Node (MTPVN) is that there is more clearance between the robot and the obstacles, and so it is safer. The accessibility graph plays an important role in motion planning for a massless mobile robot in dynamic environments. It can generate a minimum time motion in 0(n2»log(n)) computation time, where n is the number of vertices of all the polygonal obstacles. If the robot is not considered to be massless (that is, it requires time to accelerate), the space time approach becomes a 3D problem which requires exponential time and memory. A new approach is presented here based on the improved accessibility polygon and improved accessibility graph, which generates a minimum time motion for a mobile robot with mass in O((n+k)2»log(n+k)) time, where n is the number of vertices of the obstacles and k is the number of obstacles. Since k is much less than n, so the computation time for this approach is almost the same as the accessibility graph approach. The accessibility graph approach is extended to solve motion planning for robots in three dimensional environments. The three dimensional accessibility graph is constructed based on the concept of the accessibility polyhedron. Based on the properties of minimum time motion, an approach is proposed to search the three dimensional accessibility graph to generate the minimum time motion. Motion planning in binary image representation environment is also studied. Fuzzy logic based digital image processing has been studied. The concept of Fuzzy Principal Index Of Area Coverage (PIOAC) is proposed to recognise and match objects in consecutive images. Experiments show that PIOAC is useful in recognising objects. The visibility graph of a binary image representation environment is very inefficient, so the approach usually used to plan the motion for such an environment is the quadtree approach. In this research, polygonizing an obstacle is proposed. The approaches developed for various environments can be used to solve the motion planning problem without any modification. A simulation system is designed to simulate the approaches