An adaptive appearance-based map for long-term topological localization of mobile robots

"This work considers a mobile service robot which uses an appearance-based representation of its workplace as a map, where the current view and the map are used to estimate the current position in the environment. Due to the nature of real-world environments such as houses and offices, where the appearance keeps changing, the internal representation may become out of date after some time. To solve this problem the robot needs to be able to adapt its internal representation continually to the changes in the environment. This paper presents a method for creating an adaptive map for long-term appearance-based localization of a mobile robot using long-term and short-term memory concepts, with omni-directional vision as the external sensor."--publisher website

Toward an object-based semantic memory for long-term operation of mobile service robots

Throughout a lifetime of operation, a mobile service robot needs to acquire, store and update its knowledge of a working environment. This includes the ability to identify and track objects in different places, as well as using this information for interaction with humans. This paper introduces a long-term updating mechanism, inspired by the modal model of human memory, to enable a mobile robot to maintain its knowledge of a changing environment. The memory model is integrated with a hybrid map that represents the global topology and local geometry of the environment, as well as the respective 3D location of objects. We aim to enable the robot to use this knowledge to help humans by suggesting the most likely locations of specific objects in its map. An experiment using omni-directional vision demonstrates the ability to track the movements of several objects in a dynamic environment over an extended period of time.

Towards a spatial language for mobile robots

We present a framework and first set of simulations for evolving a language for communicating about space. The framework comprises two components: (1) An established mobile robot platform, RatSLAM, which has a "brain" architecture based on rodent hippocampus with the ability to integrate visual and odometric cues to create internal maps of its environment. (2) A language learning system based on a neural network architecture that has been designed and implemented with the ability to evolve generalizable languages which can be learned by naive learners. A study using visual scenes and internal maps streamed from the simulated world of the robots to evolve languages is presented. This study investigated the structure of the evolved languages showing that with these inputs, expressive languages can effectively categorize the world. Ongoing studies are extending these investigations to evolve languages that use the full power of the robots representations in populations of agents.

Flying robots to the rescue

UAVs could one day save the lives of lost civilians and those sent to find them, and a competition in outback Australia is proving how soon that day might come. We have all seen news stories of people who ventured beyond the day-to-day reach of the community and got lost: search parties are formed, aircraft drafted in, and often large sums of money expended in the quest to find them.

Phobos and deimos on Mars - two autonomous robots for the DLR SpaceBot Cup

In 2013, ten teams from German universities and research institutes participated in a national robot competition called SpaceBot Cup organized by the DLR Space Administration. The robots had one hour to autonomously explore and map a challenging Mars-like environment, find, transport, and manipulate two objects, and navigate back to the landing site. Localization without GPS in an unstructured environment was a major issue as was mobile manipulation and very restricted communication. This paper describes our system of two rovers operating on the ground plus a quadrotor UAV simulating an observing orbiting satellite. We relied on ROS (robot operating system) as the software infrastructure and describe the main ROS components utilized in performing the tasks. Despite (or because of) faults, communication loss and breakdowns, it was a valuable experience with many lessons learned.

Robots, the internet and teaching history in the age of the NBN and the Australian curriculum

Have you ever wished you were Doctor Who and could pop yourself and your students into a Tardis and teleport them to an historical event or to meet a historical figure? We all know that unfortunately time travel is not (yet) possible, but maybe student and teacher teleportation just might be – sort of. Over the past few centuries and in lieu of time travel our communities have developed museums as a means of experiencing some of our history...

Rubbing shoulders with mobile service robots

This paper is not about the details of yet another robot control system, but rather the issues surrounding realworld robotic implementation. It is a fact that in order to realise a future where robots co-exist with people in everyday places, we have to pass through a developmental phase that involves some risk. Putting a “Keep Out, Experiment in Progress” sign on the door is no longer possible since we are now at a level of capability that requires testing over long periods of time in complex realistic environments that contain people. We all know that controlling the risk is important – a serious accident could set the field back globally – but just as important is convincing others that the risks are known and controlled. In this article, we describe our experience going down this path and we show that mobile robotics research health and safety assessment is still unexplored territory in universities and is often ignored. We hope that the article will make robotics research labs in universities around the world take note of these issues rather than operating under the radar to prevent any catastrophic accidents.

Bringing the farmer perspective to agricultural robots

The research reported in this paper explores autonomous technologies for agricultural farming application and is focused on the development of multiple-cooperative agricultural robots (AgBots). These are highly autonomous, small, lightweight, and unmanned machines that operate cooperatively (as opposed to a traditional single heavy machine) and are suited to work on broadacre land (large-scale crop operations on land parcels greater than 4,000m2). Since this is a new, and potentially disruptive technology, little is yet known about farmer attitudes towards robots, how robots might be incorporated into current farming practice, and how best to marry the capability of the robot with the work of the farmer. This paper reports preliminary insights (with a focus on farmer-robot control) gathered from field visits and contextual interviews with farmers, and contributes knowledge that will enable further work toward the design and application of agricultural robotics.

Path algebra for mobile robots

In this paper, we introduce a path algebra well suited for navigation in environments that can be abstracted as topological graphs. From this path algebra, we derive algorithms to reduce routes in such environments. The routes are reduced in the sense that they are shorter (contain fewer edges), but still connect the endpoints of the initial routes. Contrary to planning methods descended from Disjktra’s Shortest Path Algorithm like D , the navigation methods derived from our path algebra do not require any graph representation. We prove that the reduced routes are optimal when the graphs are without cycles. In the case of graphs with cycles, we prove that whatever the length of the initial route, the length of the reduced route is bounded by a constant that only depends on the structure of the environment.

From vision to actions: Towards adaptive and autonomous humanoid robots

Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions.

Smooth stabilisation of nonholonomic robots subject to disturbances

In this paper, we address the problem of stabilisation of robots subject to nonholonommic constraints and external disturbances using port-Hamiltonian theory and smooth time-invariant control laws. This should be contrasted with the commonly used switched or time-varying laws. We propose a control design that provides asymptotic stability of an manifold (also called relative equilibria)-due to the Brockett condition this is the only type of stabilisation possible using smooth time-invariant control laws. The equilibrium manifold can be shaped to certain extent to satisfy specific control objectives. The proposed control law also incorporates integral action, and thus the closed-loop system is robust to unknown constant disturbances. A key step in the proposed design is a change of coordinates not only in the momentum, but also in the position vector, which differs from coordinate transformations previously proposed in the literature for the control of nonholonomic systems. The theoretical properties of the control law are verified via numerical simulation based on a robotic ground vehicle model with differential traction wheels and non co-axial centre of mass and point of contact.

Goal Seeking for Robots in Unknown Environments

We consider the problem of goal seeking by robots in unknown environments. We present a frontier based algorithm for finding a route to a goal in a fully unknown environment, where information about the goal region (GR), the region where the goal is most likely to be located, is available. Our algorithm efficiently chooses the best candidate frontier cell, which is on the boundary between explored space and unexplored space, having the maximum ``goal seeking index'', to reach the goal in minimal number of moves. Modification of the algorithm is also proposed to further reduce the number of moves toward the goal. The algorithm has been tested extensively in simulation runs and results demonstrate that the algorithm effectively directs the robot to the goal and completes the search task in minimal number of moves in bounded as well as unbounded environments. The algorithm is shown to perform as well as a state of the art agent centered search algorithm RTAA*, in cluttered environments if exact location of the goal is known at the beginning of the mission and is shown to perform better in uncluttered environments.

Nonlinear dynamics and chaotic motions in feedback-controlled two- and three-degree-of-freedom robots

The dynamics of a feedback-controlled rigid robot is most commonly described by a set of nonlinear ordinary differential equations. In this paper we analyze these equations, representing the feedback-controlled motion of two- and three-degrees-of-freedom rigid robots with revolute (R) and prismatic (P) joints in the absence of compliance, friction, and potential energy, for the possibility of chaotic motions. We first study the unforced or inertial motions of the robots, and show that when the Gaussian or Riemannian curvature of the configuration space of a robot is negative, the robot equations can exhibit chaos. If the curvature is zero or positive, then the robot equations cannot exhibit chaos. We show that among the two-degrees-of-freedom robots, the PP and the PR robot have zero Gaussian curvature while the RP and RR robots have negative Gaussian curvatures. For the three-degrees-of-freedom robots, we analyze the two well-known RRP and RRR configurations of the Stanford arm and the PUMA manipulator respectively, and derive the conditions for negative curvature and possible chaotic motions. The criteria of negative curvature cannot be used for the forced or feedback-controlled motions. For the forced motion, we resort to the well-known numerical techniques and compute chaos maps, Poincare maps, and bifurcation diagrams. Numerical results are presented for the two-degrees-of-freedom RP and RR robots, and we show that these robot equations can exhibit chaos for low controller gains and for large underestimated models. From the bifurcation diagrams, the route to chaos appears to be through period doubling.