Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

Emerging robot swarm traffic

We discuss traffic patterns generated by swarms of robots while commuting to and from a base station. The overall question is whether to explicitly organise the traffic or whether a certain regularity develops `naturally'. Human driven motorized traffic is rigidly structured in two lanes. However, army ants develop a three-lane pattern in their traffic, while human pedestrians generate a main trail and secondary trials in either direction. Our robot swarm approach is bottom-up: designing individual agents we first investigate the mathematics of cases occurring when applying the artificial potential field method to three 'perfect' robots. We show that traffic lane pattern will not be disturbed by the internal system of forces. Next, we define models of sensor designs to account for the practical fact that robots (and ants) have limited visibility and compare the sensor models in groups of three robots. In the final step we define layouts of a highway: an unbounded open space, a trail with surpassable edges and a hard defined (walled) highway. Having defined the preliminaries we run swarm simulations and look for emerging traffic patterns. Apparently, depending on the initial situation a variety of lane patterns occurs, however, high traffic densities do delay the emergence of traffic lanes considerably. Overall we conclude that regularities do emerge naturally and can be turned into an advantage to obtain efficient robot traffic

Vision and distance integrated sensor (Kinect) for an autonomous robot

This work presents an application of the Microsoft Kinect camera for an autonomous mobile robot. In order to drive autonomously one main issue is the ability to recognize signalling panels positioned overhead. The Kinect camera can be applied in this task due to its double integrated sensor, namely vision and distance. The vision sensor is used to perceive the signalling panel, while the distance sensor is applied as a segmentation filter, by eliminating pixels by their depth in the object’s background. The approach adopted to perceive the symbol from the signalling panel consists in: a) applying the depth image filter from the Kinect camera; b) applying Morphological Operators to segment the image; c) a classification is carried out with an Artificial Neural Network and a simple Multilayer Perceptron network that can correctly classify the image. This work explores the Kinect camera depth sensor and hence this filter avoids heavy computational algorithms to search for the correct location of the signalling panels. It simplifies the next tasks of image segmentation and classification. A mobile autonomous robot using this camera was used to recognize the signalling panels on a competition track of the Portuguese Robotics Open

Reactive Planning of Autonomous Vehicles for Traffic Scenarios

Autonomous vehicles operate in real time traffic scenarios and aim to reach their destination from their source in the most efficient manner possible. Research in mobile robotics provides a variety of sophisticated means with which to plan the path of these vehicles. Conversely professional human drivers usually drive using instinctive means, which enables them to reach their goal almost optimally whilst still obeying all traffic laws. In this paper we propose the use of fuzzy logic for novel motion planning. The planner is generated using an evolutionary algorithm which resembles the learning stage of professional drivers. Whether to overtake or not, is a decision which affects one’s driving and the decision is made using some deliberation. We further extend the approach to perform decision making regarding overtaking for all vehicles. Further we coordinate the motion of the vehicles at a traffic crossing to avoid any potential jam or collision. Experimental results prove that by using this approach we have been able to make the vehicles move in an optimal manner in a variety of scenarios

Look Both Ways: Intersections Of Past And Present In The Shaping Of Relations Between Cyclists, Pedestrians, And Driverless Cars

Driverless cars are expected to transform society in many ways. Since nowadays most collisions are due to human error, safety is among the most anticipated benefits of the technology. The promise of near zero fatalities on roads appears in many industry statements and government reports. Because of that, every collision, especially involving fatalities, receives much attention from the media and public. That kind of scrutiny resembles the early days of the conventional automobiles. In those days, automobiles – also called “horseless carriages” – were not well received by the majority of the population. Cars brought conflicts and fatalities on roads to a level never seen before. The automobile industry, using public relations, shifted society’s perception about who belongs to the roads, and who should be blamed for the rise of fatalities. That shift influenced legislation and tort law in motor-vehicle centric ways. It also created cities with infrastructure focused on the automobile at the expense of other means of transportation. Today, one of the most difficult challenges for driverless cars is the unpredictability of pedestrian and cyclist behaviour. To accelerate the deployment of the technology, some are considering the necessity of law enforcement against pedestrians and other street users. Centred on urban environments, pedestrians and cyclists, and with an interdisciplinary and advocacy-oriented approach, this thesis seeks to contribute to the debate about the safety and deployment of driverless cars, its influence on law and legislation, and how a car-centred view of the technology may limit its potentialities