We present the design approach and evaluation of our prototype called "Ranger". Ranger is a robotic toy box that aims to motivate young children to tidy up their room. We evaluated Ranger in 14 families with 31 children (2-10 years) using the Wizard-of-Oz technique. This case study explores two different robot behaviors (proactive vs. reactive) and their impact on children's interaction with the robot and the tidying behavior. The analysis of the video recorded scenarios shows that the proactive robot tended to encourage more playful and explorative behavior in children, whereas the reactive robot triggered more tidying behavior. Our findings hold implications for the design of interactive robots for children, and may also serve as an example of evaluating an early version of a prototype in a real-world setting.

We introduce enhanced directional self-assembly (EDSA) - a novel mechanism for morphology growth through the creation of directed connections in a self-assembling multirobot system. In our approach, a robot inviting a physical connection actively recruits the best located neighboring robot and guides the recruit to the location on its chassis where the connection is required. The proposed mechanism relies on local, high-speed communication between connection inviting robots and their recruits. Communication is based on a hybrid technology that combines radio and infrared to provide local relative positioning information when messages are transmitted between adjacent robots. Experiments with real robotic hardware show that EDSA is precise (misalignment of only 1.2° on average), robust (100% success rate for the experiments in this study) and fast (16.1 seconds on average from a distance of 80 cm). We show how the speed and precision of the new approach enable adaptive recruitment and connection in dynamic environments, a high degree of parallelism, and growth of a moving morphology.

Simultaneous localization and mapping (SLAM) is a prominent feature for autonomous robots operating in undefined environments. Applications areas such as consumer robotics appliances would clearly benefit from low-cost and compact SLAM implementations. The SLAM research community has developed several robust algorithms in the course of the last two decades. However, until now most SLAM demonstrators have relied on expensive sensors or large processing power, limiting their realms of application. Several works have explored optimizations into various directions; however none has presented a global optimization from the mechatronic to the algorithmic level. In this article, we present a solution to the SLAM problem based on the co-design of a slim rotating distance scanner, a lightweight SLAM software, and an optimization methodology. The scanner consists of a set of infrared distance sensors mounted on a contactless rotating platform. The SLAM algorithm is an adaptation of FastSLAM 2.0 that runs in real time on a miniature robot. The optimization methodology finds the parameters of the SLAM algorithm using an evolution strategy. This work demonstrates that an inexpensive sensor coupled with a low-speed processor are good enough to perform SLAM in simple environments in real time.

Collective and swarm robotics explores scenarios involving many robots running at the same time. A good platform for collective-robotic experiments should provide certain features among others: it should have a large battery life, it should be able to perceive its peers, and it should be capable of interacting with them. This paper presents the marXbot, a miniature mobile robot that addresses these needs. The marXbot uses differential-drive treels to provide rough-terrain mobility. The marXbot allows continuous experiments thanks to a sophisticated energy management and a hotswap battery exchange mechanism. The marXbot can self-assemble with peers using a compliant attachment mechanism. The marXbot provides high-quality vision, using two cameras directly interfaced with an ARM processor. Compared to the related work, the marXbot has better energy management, vision, and interaction capabilities. By allowing complex tasks in large environments for long durations, the marXbot opens new perspectives for the collective-robotic research.

During traditional open procedures, surgeons directly palpate tissues before dissecting them. In this way, they can avoid the accidental damage of hidden arteries that can lead to fatal hemorrhage. New Minimally Invasive Surgical (MIS) techniques progressively decreased the instrument access into the patient's body to reduce scars and side effects. The major drawback of these procedures is that they do not permit surgeons to perform direct tactile exploration of internal tissues. Surgeons have to rely on preoperative images and anatomical knowledge to avoid artery locations. However, the exact artery position changes depending on the patient and his posture. Hence, it is of primary importance to assist surgeons with technology that can guide them during the surgical procedure. This paper presents the design and evaluation of a tactile display that reproduces pulse-like feedback on the surgeon's fingertip. The display bandwidth and performance of the ad-hoc control unit were assessed with encouraging results. In addition, the outcome of two psychophysical studies carried out in this work validate the usability of the display in terms of user perception.

The most common ground locomotion method to make a mobile robot move is to use two-wheel drive with differential steering and a rear balancing caster. Controlling the two motors independently makes the robot non-holonomic in its motion. Such robots can work well indoor on flat surfaces and in environments adapted for wheelchairs. But the benefit of providing mobility to a robot directly relies on its locomotion capability, for handling different types of terrains (indoors or outdoors) and situations such as moving slowly or rapidly, with or without the presence of moving objects (living or not), climbing over objects and potentially having to deal with hazardous conditions. It is with this objective in mind that we designed AZIMUT. AZIMUT is a legged tracked wheeled robot capable of changing the orientation of its four articulations. Each articulation has three degrees of freedom (DOF): it can rotate 360deg around its point of attachment to the chassis, can change its orientation over 180deg, and rotate to propulse the robot.