Abstract

The structure and ion channel activity of the viral ion channels Vpu from human immunodeficiency virus type I (HIV-1) and 3a from SARS Coronavirus (SARS-CoV) have not been characterised in atomistic detail, in spite of the physiological importance of these ion channels. We have modelled several possible oligomeric states for Vpu, and carried out extensive molecular dynamics (MD) simulations in a lipid bilayer environment. Our results show that the pentamer is the most stable oligomeric form, with van der Waals interactions being the dominant force in holding together the monomeric units. The mechanism of ion conduction through the pentameric form has been investigated by umbrella sampling free energy calculations. We suggest that only one ion can pass through the channel at a time, rather than a continuous stream of ions; this is in agreement with experimental conductance studies [1]. We have also modelled possible structures for a monomeric unit of the ion channel SARS 3a, which has three helical transmembrane (TM) domains connected by loops [2]. Based on residue orientation, clusters of hydrophilic residues have been identified in each TM domain, and, by considering all possible orientations of these hydrophilic clusters, a number of monomers have been modelled and equilibrated in a membrane environment. We shall be presenting model structures of both monomeric and oligomeric states of 3a

Abstract

This paper presents an effective method of fusing appearance and geometric (homography) cues that provides for accurate and reliable floor segmentation in significantly difficult situations hitherto not demonstrated in literature. A robot equipped with a monocular camera is able to segment floors over extremely long indoor sequences, when illumination conditions contrast over a single view, when the floor and non floor regions are of same color, when the texture of floor varies over a single image, when features are lost while the robot rotates and in the presence of extremely low lying obstacles. This reliability stems from an organic blending of appearance and homography cues at various levels and most importantly through a Recursive Bayes Filter formalism. Herein the appearance and homography based error models are appropriately weighed to come up with the eventual class probability of a feature track. Equally important the paper presents ways to mitigate the problems posed by virtual plane. Virtual plane problem occurs when obstacles of very low height classified as belonging to the ground by homography. We show extensive experimental results portraying accurate and reliable segmentation in situations where virtual plane problem becomes prominent and also in other challenging situations mentioned earlier.

Abstract

A solution to the relative scale problem where reconstructed moving objects and the stationary world are represented in a unified common scale has proven equivalent to a conjecture. Motion reconstruction from a moving monocular camera is considered ill posed due to known problems of observability. We show for the first time several significant motion reconstruction of outdoor vehicles moving along non-holonomic curves and straight lines. The reconstructed motion is represented in the unified frame which also depicts the estimated camera trajectory and the reconstructed stationary world. This is possible due to our Multibody VSLAM framework with a novel solution for relative scale proposed in the current paper. Two solutions that compute the relative scale are proposed. The solutions provide for a unified representation within four views of reconstruction of the moving object and are thus immediate. In one, the solution for the scale is that which satisfies the planarity constraint of the object motion. The assumption of planar object motion while being generic enough is subject to stringent degenerate situations that are more widespread. To circumvent such degeneracies we assume that the object motion to be locally circular or linear and find the relative scale solution for such object motions. Precise reconstruction is achieved in synthetic data. The fidelity of reconstruction is further vindicated with reconstructions of moving cars and vehicles in uncontrolled outdoor scenes.

Abstract

This paper presents a simulation framework for evolution on uneven terrains for a wheeled mobile robot (WMR) such as a synchronous drive robot. The framework lends itself as a tool capable of solving various problems, such as forward kinematic-based evolution, inverse kinematic-based evolution, path planning and trajectory tracking. This framework becomes particularly useful when we understand that the evolution problem (and hence, the various associated problems based on evolution) is particularly challenging on uneven terrain. Specifically, it is entailed to bring in the contact constraints posed by the interaction of the wheel and the ground as well as the holonomic constraints as the problem is formulated in a Differential Algebraic Equation setting. The problem becomes all the more crucial as vehicles moving on uneven terrain are becoming the order of the day. Nonetheless, there has not been much literature that deals in length the various aspects that go into the framework. This paper elaborates on the various aspects of the framework, presents simulation results on uneven terrain, where the vehicle evolves without slipping, and also presents substantial quantitative analysis in regard to wheel slippage. The main contributions of this paper are the motion planning using forward kinematic framework and a new formulation of inverse kinematics for wheeled robots on uneven terrains.

Abstract

This paper presents a Field Programmable Gate Array (FPGA) based implementation of Acceleration Velocity Obstacle based Collision Avoidance for an omni-directional robot with acceleration constraint. A novel Globally Asynchronous-Locally Synchronous (GALS) architecture using hybrid parallel-pipelined design is being used for the implementation. FPGA offers highly parallel hardware architectures that are not possible on conventional high end processors or other embedded controllers. Specifically, a parallel architecture for collision avoidance is proposed that portrays the advantages of FPGA implementation over the sequential implementation for same processor or clock speed with the objective of parallelizing the computation. The proposed two-tier GALS architecture based system with hybrid parallel-pipelined architectural design when realized on FPGA shows its efficiency in terms of power, resources and response time in comparison with a conventional GALS design. Due to the asynchronous design, a good amount of logic in the hardware becomes combinational logic and hence a significant reduction in the total resource utilization and power-delay product (PDP) in the proposed architecture is observed. This paper also shows the clear advantage of using the FPGA instead of a general purpose processor for robotic system design.

Abstract

We present an autonomous system for outdoor terrain (road) mapping using a robot equipped with viable low cost sensors (2D laser scanner, cameras, odometry, gyroscope and commercial GPS). The research work on outdoor navigation with known maps has matured well in past few years, but navigation and exploration of roads in an unknown area is still emerging. The presented system is an amalgamation of various computation modules running in parallel and interacting asynchronously with each other through message queues. The goal of the system is for a vehicle to explore and build a road network graph of a given area by autonomously navigating through all the connected roads in the area. The graph nodes contain topographic and semantic properties to allow reconstruction of the road network at a later stage for easier navigation.

Abstract

In this paper, we address the problem of reactive collision avoidance among multiple robots. However we impose the constraint of continuous curvature on the collision avoidance manoeuvre which adds to the complexity of the problem but is necessary for realistic implementation of collision avoidance among multiple non-holonomic robots like tricycles and car-like. Since these non-holonomic robots cannot execute point-turn motion, performing collision avoidance with these robots while maintaining curvature continuity becomes a very challenging problem. Hence the proposed work comes as an enhancement over the existing reactive collision avoidance frameworks which completely neglect the above aspects. We modify the collision cone approach of collision avoidance to the case of multiple robots moving with non-linearly varying velocities. This is done by approximating the vehicle evolution with a smooth function represented as a linear combination of orthogonal basis functions and writing the collision avoidance condition as analytical function with respect to time. As a direct consequence of that, the reactive collision avoidance and goal-reaching could be solved as a constrained optimization problem. The theory is substantiated by extensive simulations for various bench-mark cases.

Abstract

Over the past couple of years, with the development of efficient control algorithms, micro aerial vehicles have come into the picture. In this paper, we consider the problem of creating a map of an indoor environment which provides more information than a 2D map and at the same time is more accurate than the contemporary 3D mapping algorithms. We propose a novel collaborative system, consisting of an unmanned ground vehicle and a micro aerial vehicle, which is used to create augmented 2D maps using the distinct sensing capabilities of these two robots. This system works in a collaborative manner such that the two robots complement each others movement and sensing capabilities.

Abstract

This paper presents a method to capture the orbiting objects using a robotic system mounted on a service satellite. The main objective is to manipulate the robot such that no reaction moment gets transferred to the base satellite. This will avoid use of any attitude controller resulting in fuel savings. Note that the constraints leading to zero reaction moment are nonholonomic, and this makes path planning a complex problem. In this work, first a method based on holonomic distribution of the nonholonomic constraints is discussed. As this method exploits constraints in terms of joint velocities, it does not always ensure successful capture. Next, a method based on task-level constraints, written in terms of end-effector's velocities, has been illustrated. It is shown that the path planned using this method has several singular points. In order to overcome disadvantages of the above two methods a novel approach is proposed which uses holonomic distribution to reach closer to the target and task-level constraints to finally capture the target. Efficacy of the method is shown using a 3-link robot mounted on a service satellite.

Abstract

Single camera mobile robots, wherein the single camera becomes the quintessential sensor for robotic tasks such as localization, mapping and obstacle avoidance are challenging. From such a standpoint, we demonstrate a dense reconstruction as conducted by a navigating robot with a monocular camera. Unlike most other dense reconstruction methods this approach first identifies planar areas through homography. These segments are tracked over multiple views with homography based dense correspondences. The tracked correspondences are reconstructed within a VSLAM formulation, wherein the dense reconstructed points get added to the existing SLAM computed structure. The dense structure is further refined using a modified Bundle Adjustment which minimizes projection error in 3D to align with a inferred model of the scene. A mobile robot can thus make use of the reconstructed ground plane and planar obstacles to compute a collision free trajectory.