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We describe the National Museum of Mathematics's Robot Swarm exhibit and our approach for achieving a reliable system for collision avoidance. The Robot Swarm exhibit allows visitors to program behaviors and interact with a “swarm” of small robots. The exhibit supports extended unattended run times, continuous interaction with the public and the demonstration of evocative group behaviors. The exhibit...
Navigation of cluttered underwater environments remains to this day a challenging task in mobile robotics. Applying an electric field to a mobile robot's direct environment and measuring perturbations of this field, one is able to detect the presence of foreign objects in close proximity of the system. In addition, one is also able to infer a range of information relative to the detected objects,...
This paper proposes a method called Segmentation-adaptive Pseudospectral collocation to address the problem of safe trajectory generation in missions with cooperating multiple aerial vehicles. Pseudospectral collocation can generate optimized collision-free trajectories, but for multiple aerial vehicles it cannot guarantee that the safety separation distance is maintained in the whole trajectories,...
This paper presents a novel, decentralized, control-theoretic approach to address collision avoidance for multi-robot systems. We create a virtual obstacle at the mean position of the robots. A control is be designed such that each robot will avoid the closest obstacle when a collision is possible. The closest obstacle can be the virtual obstacle or the nearest robot. We present two such control laws...
We present a new approach to the design of smooth trajectories for quadrotor unmanned aerial vehicles (UAVs), which are free of collisions with obstacles along their entire length. To avoid the non-convex constraints normally required for obstacle-avoidance, we perform a mixed-integer optimization in which polynomial trajectories are assigned to convex regions which are known to be obstacle-free....
High speed, low latency obstacle avoidance is essential for enabling Micro Aerial Vehicles (MAVs) to function in cluttered and dynamic environments. While other systems exist that do high-level mapping and 3D path planning for obstacle avoidance, most of these systems require high-powered CPUs on-board or off-board control from a ground station.
We present a novel algorithm to compute a gradient-continuous penetration depth (PhongPD) between two interpenetrated polygonal models. Our penetration depth (PD) formulation ensures separating the intersected models by translation, and the amount of such translation is close to an optimal motion to resolve interpenetration in most cases. In order to achieve the gradient-continuity in our algorithm,...
This paper presents a fast collision-detection method for sampling-based motion planners based on bounding volume hierarchies in workspace-time space. By introducing time as an additional dimension to the robot's workspace, the method is able to quickly evaluate time-indexed candidate trajectories for collision with the known future motions of other agents. The approach makes no assumptions on the...
This paper considers the problem of approximating a kernel matrix in an autoregressive Gaussian process regression (AR-GP) in the presence of measurement noises or natural errors for modeling complex motions of pedestrians in a crowded environment. While a number of methods have been proposed to robustly predict future motions of humans, it still remains as a difficult problem in the presence of measurement...
Our abilities in scene understanding, which allow us to perceive the 3D structure of our surroundings and intuitively recognise the objects we see, are things that we largely take for granted, but for robots, the task of understanding large scenes quickly remains extremely challenging. Recently, scene understanding approaches based on 3D reconstruction and semantic segmentation have become popular,...
In this paper we present a dense visual odometry system for RGB-D cameras performing both photometric and geometric error minimisation to estimate the camera motion between frames. Contrary to most works in the literature, we parametrise the geometric error by the inverse depth instead of the depth, which translates into a better fit of the distribution of the geometric error to the used robust cost...
This paper is about life-long vast-scale localisation in spite of changes in weather, lighting and scene structure. Building upon our previous work in Experience-based Navigation [1], we continually grow and curate a visual map of the world that explicitly supports multiple representations of the same place. We refer to these representations as experiences, where a single experience captures the appearance...
This paper presents the first method to compute dense scene flow in real-time for RGB-D cameras. It is based on a variational formulation where brightness constancy and geometric consistency are imposed. Accounting for the depth data provided by RGB-D cameras, regularization of the flow field is imposed on the 3D surface (or set of surfaces) of the observed scene instead of on the image plane, leading...
The stereo correspondence problem is still a highly active topic of research with many applications in the robotic domain. Still many state of the art algorithms proposed to date are unable to reasonably handle high resolution images due to their run time complexities or memory requirements. In this work we propose a novel stereo correspondence estimation algorithm that employs binary locality sensitive...
In this paper, we propose a resource-efficient system for real-time 3D terrain reconstruction and landing-spot detection for micro aerial vehicles. The system runs on an on-board smartphone processor and requires only the input of a single downlooking camera and an inertial measurement unit. We generate a two-dimensional elevation map that is probabilistic, of fixed size, and robot-centric, thus,...
This work integrates visual and physical constraints to perform real-time depth-only tracking of articulated objects, with a focus on tracking a robot's manipulators and manipulation targets in realistic scenarios. As such, we extend DART, an existing visual articulated object tracker, to additionally avoid interpenetration of multiple interacting objects, and to make use of contact information collected...
In this paper, we propose a novel approach for generating generic object candidates for object discovery and recognition in continuous monocular video. Such candidates have recently become a popular alternative to exhaustive window-based search as basis for classification. Contrary to previous approaches, we address the candidate generation problem at the level of entire video sequences instead of...
In this paper we address the problem of dense depth map estimation from sparse noisy range data to reconstruct large heterogeneous outdoor scenes. We propose a surface inpainting solution through energy minimisation with an adaptive selection of surface regularisers among a set of well known convex and non-convex regularisers. In fact, the selection of norm is pivotal with respect to the intrinsic...
Precise manipulation of microparticles has received considerable attention for its great potential applications to clinical medicine. Among the existing manipulation techniques, the method of magnetic force based manipulation exhibits great advantages for its minimally-invasive feature and insensitivity to biological substance, making it ideally suitable to in vivo environment. On the other hand,...
This is the first demonstration of a modular and reconfigurable magnetic-manipulation system with integral ferromagnetic material. This system—which includes multiple Omnimagnets, each comprising three orthogonal solenoids and a spherical ferromagnetic core—is capable of dexterous manipulation of a magnetic tool. The magnetization coupling of an arbitrary arrangement of spherical ferromagnetic cores...
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