Enabling robotic autonomy in challenging environments; an algorithmic approach

我的工作集中在推导算法解决方案，通过智能决策、协作和与计算组其他成员的信息交换来增强代理的自主性。代理可以是传感器网络中的节点、移动机器人或机器人航天器。当机器人在水下或太空等具有挑战性的环境中操作时，自主能力尤为重要。特别是行星探测和水下机器人都受到同样的限制，因为与人类操作员的通信是断断续续的，而且带宽很低。为了促进自主性，任何机器人系统都必须解决以下基本问题：根据周围环境估计它们的状态；模拟他们周围的世界；并以最佳方式规划他们的任务。在提议的研究中，我计划扩展我在三维运动机器人状态估计方面的工作，使用各种技术，如粒子滤波器和扩展卡尔曼滤波器。我还计划开发使用不规则三角形网格的环境建模新技术。在机器人社区中，前两个组件通常统称为同步定位和映射（SLAM）。此外，在我早期的工作中，以及其他研究人员已经证明，智能代理之间的协作大大提高了它们的能力。因此，我未来的计划是将单机器人行星探测算法扩展到多机器人。

My work is centred on deriving algorithmic solutions that enhance an agent's autonomy through intelligent decision-making, collaboration and information exchange with the other members of the computational group. The agents may be nodes in a sensor network, mobile robots, or robotic spacecraft. Autonomy capabilities are especially important when robots operate in challenging environments such as underwater or in space. In particular both planetary exploration and underwater robotics suffer from the same limitations as communication with a human operator is intermittent and with low bandwidth. In order to facilitate autonomy any robotic system must address the following fundamental problems: estimate their state with respect to the surrounding environment; model the world around them; and plan their tasks in an optimal manner. In the proposed research I am planning to extend my work on state estimation for robots moving in three dimensions, using a variety of techniques such as Particle filters and Extended Kalman Filters. I am also planning to develop new techniques for environment modelling using irregular triangular meshes. The previous two components are usually termed together as Simultaneous Localization and Mapping (SLAM) in the robotics community. Moreover, it has been demonstrated in my earlier work, as well as, by other researchers that collaboration between intelligent agents greatly enhances their capabilities. Therefore in my future plans is the extension of single robot planetary exploration algorithms to multiple robots.