The exploration phase of mapping is important, it is how the robots go about maximising coverage and moving through the environment in a coordinated and efficient fashion. Exploration strategies are largely Deliberative or reactive (i.e. plan decisions and paths for the future vs, reacting to obstacles and presence of other robots/ external stimuli as and when they appear), a comparison between these two techniques, and a hybrid employed for robot foraging, can be found in work by Carpin et al. [43]. The ‘reactive virtual forces’ framework outlined in chapter five of this thesis is, as the name suggests, reactive in nature. The nuclear cave environment is cluttered, making path planning difficult. Therefore, it seems prudent to utilise a reactive control method so that robots may avoid obstacles as they arise, whilst continuing the mapping effort.
If the environment is known then the map can be represented as a graph and the exploration problem becomes the travelling salesman problem of minimising the distance travelled between nodes [35]. However, in an unknown environment only a partial map may have been generated, in this situation it is useful to implement frontier cells [264]. The use of frontier cells requires that a map be divided into a grid. A frontier cell is then a cell that is known and is next to an unknown cell. The basic idea of using this for exploration is that a robot should move to such a cell in order to maximise its knowledge gain. This is often a trade-off between the utility of the cell, a heuristic measure of how much information will be gained from it, and the cost of the cell, which is usually the distance to it [36]. It is possible to utilise a bidding system to ascertain which member of a swarm will attain the most utility from a cell for the least cost [216]. This method allows for robots to continuously be moving to new, unexplored areas. The ‘reactive virtual forces’ framework utilises a force akin to the strong nuclear force to attract robots to the frontier cells of an occupancy grid [28], this method will be outlined in chapter five of this thesis, and provides a useful tool for the exploration and mapping of a nuclear cave environment.
Stachniss et al. also use the information gain of a robot in order to guide exploration [226]. In this work the entropy changes of the system, given a certain action, are calculated. The entropy change is calculated by integrating over the robot’s world model, given all possible measurement sequences. Such modelling can become computationally complex due to the need for ray-casting.
Dudek et al. show that if a robot does not have a compass or method for determining its orientation, then the exploration problem is unsolvable [72]. It is discussed that mapping using dead reckoning alone is not sufficient, due to the accumulation in errors. The authors put forward the use of markers that may be placed and picked up by the robot in order to provide landmarks for mapping. This provides motivation for the use of landmarks in the exploration task, which will be used with the EKF filter in chapter six of this thesis, to aid in localisation and mapping of
a nuclear cave environment.
So far, single robot exploration strategies have been examined; by and large it is possible implement such strategies using multiple communicating agents in order to increase efficiency. However, strategies have been designed and tested on swarms of robots, which will be discussed subsequently.
Marjovi et al. use multiple robots to map and explore an unknown environment, whilst minimising exploration time [155]. Agents aim to explore different areas of the map to identify fire sources. Potential fields are used to enable obstacle avoidance and to attract the robots to goals, such as the frontier of exploration. Khepera robots with known positions are used to test the algorithm. ‘Reactive virtual forces’ follows a similar paradigm to that discussed in work by Marjovi et al.: potential fields are used to attract the robot to exploration goals; and repel them away from obstacles. The differences are that the ‘reactive virtual forces’ framework is grounded in real physical forces and requires less communication overhead. In addition, simultaneous localisation and mapping is examined with the ’reactive virtual forces’ framework, as shall be discussed in chapter six. Finally Marjovi et al. examine the use of their virtual fields on a group of homogeneous robots, whilst ’reactive virtual forces’ are examined with homogeneous and heterogeneous robots. This work shows that it is possible to use potential fields for robotic exploration, providing motivation for ‘reactive virtual forces’ whilst leaving open research questions.
Couceiro et al. extend two instances of particle swarm optimisation, to allow for inclusion of obstacle avoidance [53]. The algorithms use social inclusion and exclusion to aid in a multi-robot exploration task. This is instigated through the deleting and spawning of particles within the swarm. The algorithm was tested in MATLAB on a simulated swarm. It was found that the use of inclusion and exclusion criteria increased the performance of the particle swarm exploration algorithm, whilst exploring an unknown environment. This work shows that MATLAB can be a powerful tool in assessing the quality of algorithms and provides motivation for its use in this project to test the ‘reactive virtual forces’ algorithm.
An alternative to frontier-based exploration is provided by Wurm et al [261]. In this work the exploration space is divided into sections, such as rooms, for individual robots in the team to explore. Segmentation is used in the hope of reducing the overall search time. Pioneer II robots are used to test the algorithm, under the assumption that the absolute position of robots is known. Map segmentation provides an interesting alternative to frontier-based exploration; however, it requires that a partial map of the environment is known a priori. This is not possible within a nuclear cave, as very little could be known before entry about the map, even as little as only knowing the perimeter of the room.
An interesting approach to multi-robot exploration is provided by Zlot et al. [275]. This work implements a market economy to allow robots to exchange services and maintain ‘profitability’ in the task of exploration. An operator executive is utilised to represent the desires of the user,
which in turn pays revenue to individual robots for information about the environment. Through the sharing of price information, coordination is achieved. Pioneer robots are used to construct occupancy grids of the environment and it was found that allowing robots to negotiate, increased the exploration efficiency. Such a bidding system could be imagined for use with a heterogeneous swarm, to allow for indirect encoding of each members abilities. This would then prove an interesting method for use in a nuclear cave environment.
Finally, Burgard et al. investigate the coordination of multi-robot teams for exploration of an unknown environment, focussing on the selection of targets points for individual robots [36] [35]. Selection of these points considers the cost and utility of visitation. The work is first discussed under the assumption of global communication, followed by a discussion of extension to the limited communication situation. Deciding which members of the swarm should examine which areas is a useful tool to increase the efficiency of exploration. Though this is not directly examined in the ‘reactive virtual forces’ framework outlined in chapter five of this thesis, it is indirectly achieved through the entry points of robots.
Overall, exploration is a well-researched area within mobile and swarm robotics. This section has shown the use of potential fields, frontier cells and MATLAB simulation as tools to implement and investigate exploration in groups of robots. Novel areas for research, under-investigated in the literature include: the use of potential fields for heterogeneous robot exploration, the use of SLAM techniques in potential fields exploration, investigating the value of utilising multiple forces grounded in physics and the application to the exploration of a nuclear cave environment. Thus, the use of ‘reactive virtual forces’ in exploration of a nuclear cave environment shows itself to be a viable and novel source for investigation.