help me the innovative projects on embedded or robotics

The ants foraging activity can be adapted for differentapplications of robotic swarm intelligence.

Rewired: unlocking the next generation of smart robotics

invests for the long term in fundamental technologies that together lay the foundation for smart robotics, while simultaneously leveraging them for our studio, which targets persistent market gaps that

The hardware was designedwith the emphasis on system flexibility for swarm application drawing attention to powerreduction and battery life.

How Switzerland Became The Silicon Valley Of Robotics - Forbes

A cleaning robot has a bounded amount of memory; it can only observe the state of the floor in its immediate surroundings and decide on its movement based on these observations.

The ants'foraging activities were studied in greater detail with the emphasis on a layered control systemdesigned implementation in a robotic agent.

different representational formats of robotics and AI. Embodied robots As a result of this thesis, it will be shown that robot perception can particularly gain.

Working ants andbees has captivated researchers for centuries, with the ant playing a major role in shaping thefuture of robotic swarm applications.

Dissertation Or Thesis On Robotics

Before the robot can actually grasp and excert forces onto an object, it needs to create hypotheses where and how to grasp. The focus of this thesis would be on

Swarm robotics Inspired by self-organisation of ..

In the field of robotics, there is a growing need to provide robots with the ability in this thesis are expected to contribute to the needs in advanced controller

Research papers on swarm robotics

In the field of robotics, there is a growing need to provide robots with the ability in this thesis are expected to contribute to the needs in advanced controller

Multi-robot and swarm olfactory search, PhD Thesis

Swarm robotics is the study of large groups of relatively homogeneous robots and their task solving capabilities. The robots of a swarm robotic system are relatively simple and incapable when compared to the tasks that they are expected to accomplished [10]. Thus, it is important to have enough units and a distributed control law that is effective. Because the individual behaviour of social insects often inspires the control law design in swarm robotic systems, the control law of individual robots is usually referred to as individual behaviour. The behaviours of the robots are usually identical and make use of only local information. Combining these features, a swarm robot system offers potential advantages in robustness, flexibility and scalability [11]. However, the cause-effect of the individual behaviour in a swarm robot system is not straight forward when compared to the control

Research papers on swarm robotics - …

This thesis investigates the potential of social robots in education and develops the concept of Persuasive Educational and Entertainment Robotics (PEERs).

Swarm intelligence in autonomous collective robotics

Swarm intelligence is a new research paradigm that offers novel approaches for studying and solving distributed problems using solutions inspired by social insects and other natural behaviors of vertebrates. In this thesis, we present methodologies for modeling artificial, mobile systems within the swarm intelligence framework. The proposed methodologies provide guidelines in the study and design of artificial swarm systems for the following two classes of experiments: distributed sensing and distributed manipulation.Event discovery and information dissemination through local communication in artificial swarm systems present similar characteristics as natural phenomena such as foraging and food discovery in insect colonies and the spread of infectious diseases in animal populations, respectively. We show that the artificial systems can be described in similar mathematical terms as those used to describe the natural systems. The proposed models can be classified in two main categories: non-embodied and embodied models. In the first category agents are modeled as mobile bodiless points, whereas the other models take into account the physical interference between agents resulting from embodiment. Furthermore, within each category, we distinguish two subcategories: spatial and nonspatial models. In the spatial models we keep track of the trajectory of each agent, the correlation between the positions occupied by the agents over consecutive time steps, or make use of the spatial distribution resulting from the movement pattern of the agents. In the nonspatial models we assume that agents hop around randomly and occupy independent positions over consecutive time steps.In our description of distributed manipulation in swarm robotic systems we present two case studies of non-collaborative and collaborative manipulations, respectively. The general approach proposed here consists of first representing the group behavior of the active agents with a Finite State Machine (FSM) then describing mathematically the dynamics of the group. The first case study is the aggregation experiment that consists of collecting and gathering objects scattered around an enclosed arena. We present a macroscopic model that accurately captures the dynamics of the experiment and a suite of threshold-based, scalable, and fully distributed algorithms for allocating the workers to the task optimally. The second case study is that of the stick-pulling experiment in which a group of robots is used to pull sticks from the ground. This task requires the collaborative effort of two robots to be successful. Here, we present a discrete-time macroscopic model that helps us uncover counter-intuitive behaviors that result from collaboration between the agents.We complete each proposed modeling methodology by showing how the parameters of the models can be calculated using solely the characteristics of the environment and those of the agents and by analyzing the constraints and limitations of the different models. Finally, we use different tools (simulations and real robots) to validate the proposed models.