Coverage & cooperation: Completing complex tasks as quickly as possible using teams of robots

As the robotics industry grows and robots enter our homes and public spaces, they are increasingly expected to work in cooperation with each other. My thesis focuses on multirobot planning, specifically in the context of coverage robots, such as robotic lawnmowers and vacuum cleaners. Two problems unique to multirobot teams are task allocation and search. I present a task allocation algorithm which balances the workload amongst all robots in the team with the objective of minimizing the overall mission time. I also present a search algorithm which robots can use to find lost teammates. It uses a probabilistic belief of a target robot’s position to create a planning tree and then searches by following the best path in the tree. For robust multirobot coverage, I use both the task allocation and search algorithms. First the coverage region is divided into a set of small coverage tasks which minimize the number of turns the robots will need to take. These tasks are then allocated to individual robots. During the mission, robots replan with nearby robots to rebalance the workload and, once a robot has finished its tasks, it searches for teammates to help them finish their tasks faster

Radio and Audio Strategies for External Cultural Relations: conference report, Berlin, 24/25 October 2013

Radio and online audio-formats are valuable instruments for international cultural work, and for education and development programmes. However, political developments following the end of the Cold War and the rise of satellite TV and online media have brought with them far-reaching cuts in the radio programming of international broadcasters, and led to fundamental changes in the way radio and audio programmes are produced and distributed. Major western broadcasters, such as BBC World Service, BBG, RFI and DW, have limited their shortwave services to a small selection of countries, mainly in Africa and parts of Asia, where the infrastructure does not offer real alternatives for addressing the respective target groups. In these regions, radio still plays a vital role, not only for reasons related to infrastructure, but also because a great number of illiterate listeners can access information, knowledge and education best via audio. Traditional radio production and terrestrial transmission are also useful and efficient tools in media development work, as they can reach out into remote or rural areas and empower people to strengthen their community and cultural identity. But radio’s relevance goes beyond the local needs of regions that have not kept pace with the rate of recent technological change and media innovation. Radio has been at the core of international broadcasting right from the start, and now that it has become one element in a new mix of media, it turns out that there are some attractive core qualities of radio and audio that remain. These qualities are: 1. the direct and emotional impact of the human voice, 2. radio’s well-established culture of dialogue, 3. its potential to involve listeners as coproducers, 4. the flexibility, mobility and comparatively low production costs of audio, 5. its ability to subvert censorship

Innovative Tokyo

This paper compares and contrasts Tokyo's innovation structure with the industrial districts model and the international hub model in the literature on urban and regional development. The Tokyo model embraces and yet transcends both industrial districts and international hub models. The paper details key elements making up the Tokyo model-organizational knowledge creation, integral and co-location systems of corporate R&D and new product development, test markets, industrial districts and clusters, participative consumer culture, continuous learning from abroad, local government policies, the national system of innovation, and the historical genesis of Tokyo in Japan's political economy. The paper finds that the Tokyo model of innovation will continue to evolve with the changing external environment, but fundamentally retains its main characteristics. The lessons from the Tokyo model is that openness, a diversified industrial base, the continuing development of new industries, and an emphasis on innovation, all contribute to the dynamism of a major metropolitan region.Labor Policies,Environmental Economics&Policies,Public Health Promotion,ICT Policy and Strategies,Agricultural Knowledge&Information Systems,ICT Policy and Strategies,Environmental Economics&Policies,Health Monitoring&Evaluation,Agricultural Knowledge&Information Systems,Innovation

Human Motion Trajectory Prediction: A Survey

With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots and advanced surveillance systems. This paper provides a survey of human motion trajectory prediction. We review, analyze and structure a large selection of work from different communities and propose a taxonomy that categorizes existing methods based on the motion modeling approach and level of contextual information used. We provide an overview of the existing datasets and performance metrics. We discuss limitations of the state of the art and outline directions for further research.Comment: Submitted to the International Journal of Robotics Research (IJRR), 37 page

Avoiding target congestion on the navigation of robotic swarms

Robotic swarms are decentralized systems formed by a large number of robots. A common problem encountered in a swarm is congestion, as a great number of robots often must move towards the same region. This happens when robots have a common target, for example during foraging or waypoint navigation. We propose three algorithms to alleviate congestion: in the first, some robots stop moving towards the target for a random number of iterations; in the second, we divide the scenario in two regions: one for the robots that are moving towards the target, and another for the robots that are leaving the target; in the third, we combine the two previous algorithms. We evaluate our algorithms in simulation, where we show that all of them effectively improve navigation. Moreover, we perform an experimental analysis in the real world with ten robots, and show that all our approaches improve navigation with statistical significance