Collision-free motion of two robot arms in a common workspace

Collision-free motion of two robot arms in a common workspace is investigated. A collision-free motion is obtained by detecting collisions along the preplanned trajectories using a sphere model for the wrist of each robot and then modifying the paths and/or trajectories of one or both robots to avoid the collision. Detecting and avoiding collisions are based on the premise that: preplanned trajectories of the robots follow a straight line; collisions are restricted to between the wrists of the two robots (which corresponds to the upper three links of PUMA manipulators); and collisions never occur between the beginning points or end points on the straight line paths. The collision detection algorithm is described and some approaches to collision avoidance are discussed

Towards building a team of intelligent robots

Topics addressed include: collision-free motion planning of multiple robot arms; two-dimensional object recognition; and pictorial databases (storage and sharing of the representations of three-dimensional objects)

Uncertainty and social considerations for mobile assistive robot navigation

An increased interest in mobile robots has been seen over the past years. The wide range of possible applications, from vacuum cleaners to assistant robots, makes such robots an interesting solution to many everyday problems. A key requirement for the mass deployment of such robots is to ensure they can safely navigate around our daily living environments. A robot colliding with or bumping into a person may be, in some contexts, unacceptable. For example, if a robot working around elderly people collides with one of them, it may cause serious injuries. This thesis explores four major components required for effective robot navigation: sensing the static environment, detection and tracking of moving people, obstacle and people avoidance with uncertainty measurement, and basic social navigation considerations. First, to guarantee adherence to basic safety constraints, sensors and algorithms required to measure the complex structure of our daily living environments are explored. Not only do the static components of the environment have to be measured, but so do any people present. A people detection and tracking algorithm, aimed for a crowded environment is proposed, thus enhancing the robot's perception capabilities. Our daily living environments present many inherent sources of uncertainty for robots, one of them arising due to the robot's inability to know people's intentions as they move. To solve this problem, a motion model that assumes unknown long-term intentions is proposed. This is used in conjunction with a novel uncertainty aware local planner to create feasible trajectories. In social situations, the presence of groups of people cannot be neglected when navigating. To avoid the robot interrupting groups of people, it first needs to be able to detect such groups. A group detector is proposed which relies on a set of gaze- and geometric-based features. Avoiding group disruption is finally incorporated into the navigation algorithm by means of taking into account the probability of disrupting a group's activities. The effectiveness of the four different components is evaluated using real world and simulated data, demonstrating the benefits for mobile robot navigation.Open Acces

Dynamic Movement Primitives: Volumetric Obstacle Avoidance Using Dynamic Potential Functions

Obstacle avoidance for DMPs is still a challenging problem. In our previous work, we proposed a framework for obstacle avoidance based on superquadric potential functions to represent volumes. In this work, we extend our previous work to include the velocity of the trajectory in the definition of the potential. Our formulations guarantee smoother behavior with respect to state-of-the-art point-like methods. Moreover, our new formulation allows to obtain a smoother behavior in proximity of the obstacle than when using a static (i.e. velocity independent) potential. We validate our framework for obstacle avoidance in a simulated multi-robot scenario and with different real robots: a pick-and-place task for an industrial manipulator and a surgical robot to show scalability; and navigation with a mobile robot in dynamic environment.Comment: Preprint for Journal of Intelligent and Robotic System

A non-holonomic, highly human-in-the-loop compatible, assistive mobile robotic platform guidance navigation and control strategy

The provision of assistive mobile robotics for empowering and providing independence to the infirm, disabled and elderly in society has been the subject of much research. The issue of providing navigation and control assistance to users, enabling them to drive their powered wheelchairs effectively, can be complex and wide-ranging; some users fatigue quickly and can find that they are unable to operate the controls safely, others may have brain injury re-sulting in periodic hand tremors, quadriplegics may use a straw-like switch in their mouth to provide a digital control signal. Advances in autonomous robotics have led to the development of smart wheelchair systems which have attempted to address these issues; however the autonomous approach has, ac-cording to research, not been successful; users reporting that they want to be active drivers and not passengers. Recent methodologies have been to use collaborative or shared control which aims to predict or anticipate the need for the system to take over control when some pre-decided threshold has been met, yet these approaches still take away control from the us-er. This removal of human supervision and control by an autonomous system makes the re-sponsibility for accidents seriously problematic. This thesis introduces a new human-in-the-loop control structure with real-time assistive lev-els. One of these levels offers improved dynamic modelling and three of these levels offer unique and novel real-time solutions for: collision avoidance, localisation and waypoint iden-tification, and assistive trajectory generation. This architecture and these assistive functions always allow the user to remain fully in control of any motion of the powered wheelchair, shown in a series of experiments

A Robust Reactive Static Obstacle Avoidance System for Surface Marine Vehicles

This paper is centered on the guidance systems used to increase the autonomy of unmanned surface vehicles (USVs). The new Robust Reactive Static Obstacle Avoidance System (RRSOAS) has been specifically designed for USVs. This algorithm is easily applicable, since previous knowledge of the USV mathematical model and its controllers is not needed. Instead, a new estimated closed-loop model (ECLM) is proposed and used to estimate possible future trajectories. Furthermore, the prediction errors (due to the uncertainty present in the ECLM) are taken into account by modeling the USV's shape as a time-varying ellipse. Additionally, in order to decrease the computation time, we propose to use a variable prediction horizon and an exponential resolution to discretize the decision space. As environmental model an occupancy probability grid is used, which is updated with the measurements generated by a LIDAR sensor model. Finally, the new RRSOAS is compared with other SOA (static obstacle avoidance) methods. In addition, a robustness study was carried out over a set of random scenarios. The results obtained through numerical simulations indicate that RRSOAS is robust to unknown and congested scenarios in the presence of disturbances, while offering competitive performance with respect to other SOA methods

Time-delayed autosynchronous swarm control

In this paper a general Morse potential model of self-propelling particles is considered in the presence of a time-delayed term and a spring potential. It is shown that the emergent swarm behavior is dependent on the delay term and weights of the time-delayed function which can be set to induce a stationary swarm, a rotating swarm with uniform translation and a rotating swarm with a stationary center-of-mass. An analysis of the mean field equations shows that without a spring potential the motion of the center-of-mass is determined explicitly by a multi-valued function. For a non-zero spring potential the swarm converges to a vortex formation about a stationary center-of-mass, except at discrete bifurcation points where the center-of-mass will periodically trace an ellipse. The analytical results defining the behavior of the center-of-mass are shown to correspond with the numerical swarm simulations