Behavioral expression of emotions and non-invasive assessment of physiological correlates in dogs (Canis familiaris)

The aim of this thesis was to validate the use of infrared thermography (IRT) to non-invasively measure emotional reactions to different situations in pet dogs (Canis familiaris). A preliminary test, aimed to evaluate the correlation between eye-temperature and rectal temperature in dog, was performed. Then, in three different situations, negative (veterinary visit), positive (palatable food rewards), and mildly stressing followed by mildly positive (separation from and reunion with the owner), variations in heat emitted from lacrimal caruncle (referred to as eye temperature) were measured with an infrared thermographic camera. In addition, heart rate and heart rate variability parameters were collected using a non-invasive heart rate monitor designed for human use and validated on dogs. All experiments were video recorded to allow behavioral coding. During the negative situation dogs’ level of activity and stress related behaviors varied across compared to the baseline and dogs showed an increase in eye temperature despite having a significant decrease in the level of activity. The positive situation was characterized by a peak in eye temperature and mean HR and dogs engaged in behaviors indicating a positive arousal, focusing on food treats and tail wagging but there were not variations in HRV during stimulation but only an increment in SDNN immediately after the stimulus. In the separation from and reunion with the owner dogs’ eye temperature and mean HR did not vary neither in the stressful nor in the positive situations, RMSSD increased after the positive episode, SDNN dropped during the two stimulations and it increased after the stimulations. During the separation from the owner dogs were mainly directed to the door or to the experimenter while during the reunion with the owner dogs were focused mainly on the owner and on the environment, exhibiting safe base effect. A different approach was used to assess the welfare of shelter dogs. Dogs were implanted with a telemeter and after implantation dogs were housed in sequence in four different situations lasting 1 week: alone, alone with toys and a stretch cot for sleeping, with an unknown, spayed, female, and alone with a daily 2-hours interaction with an experimenter. Two different approaches were tried: partially random extracted fragments from every week, behaviors from 8 a.m. to 4 p.m. were continuous during baseline and the female situation. Results showed different reactions by dogs to the different situations and interestingly not all enrichments were enjoyed by the dogs improving their welfare. Overall results suggest that IRT may represent a useful tool to investigate emotional reactions in dogs. Nevertheless, further research is needed to establish the specificity and sensivity of IRT in this context and to assess how different dogs’ characteristics, breed, previous experience and the valence and arousal elicited by the stimulus could influence the magnitude and type of the response. The role of HRV in understanding emotional valence and the one of telemeters in understanding long-term effects on sheltered dogs’ welfare is also discussed.

Designing a Computer Vision System for Underwater Robotic Interventions

This thesis deals with the challenging problem of designing systems able to perceive objects in underwater environments. In the last few decades research activities in robotics have advanced the state of art regarding intervention capabilities of autonomous systems. State of art in fields such as localization and navigation, real time perception and cognition, safe action and manipulation capabilities, applied to ground environments (both indoor and outdoor) has now reached such a readiness level that it allows high level autonomous operations. On the opposite side, the underwater environment remains a very difficult one for autonomous robots. Water influences the mechanical and electrical design of systems, interferes with sensors by limiting their capabilities, heavily impacts on data transmissions, and generally requires systems with low power consumption in order to enable reasonable mission duration. Interest in underwater applications is driven by needs of exploring and intervening in environments in which human capabilities are very limited. Nowadays, most underwater field operations are carried out by manned or remotely operated vehicles, deployed for explorations and limited intervention missions. Manned vehicles, directly on-board controlled, expose human operators to risks related to the stay in field of the mission, within a hostile environment. Remotely Operated Vehicles (ROV) currently represent the most advanced technology for underwater intervention services available on the market. These vehicles can be remotely operated for long time but they need support from an oceanographic vessel with multiple teams of highly specialized pilots. Vehicles equipped with multiple state-of-art sensors and capable to autonomously plan missions have been deployed in the last ten years and exploited as observers for underwater fauna, seabed, ship wrecks, and so on. On the other hand, underwater operations like object recovery and equipment maintenance are still challenging tasks to be conducted without human supervision since they require object perception and localization with much higher accuracy and robustness, to a degree seldom available in Autonomous Underwater Vehicles (AUV). This thesis reports the study, from design to deployment and evaluation, of a general purpose and configurable platform dedicated to stereo-vision perception in underwater environments. Several aspects related to the peculiar environment characteristics have been taken into account during all stages of system design and evaluation: depth of operation and light conditions, together with water turbidity and external weather, heavily impact on perception capabilities. The vision platform proposed in this work is a modular system comprising off-the-shelf components for both the imaging sensors and the computational unit, linked by a high performance ethernet network bus. The adopted design philosophy aims at achieving high flexibility in terms of feasible perception applications, that should not be as limited as in case of a special-purpose and dedicated hardware. Flexibility is required by the variability of underwater environments, with water conditions ranging from clear to turbid, light backscattering varying with daylight and depth, strong color distortion, and other environmental factors. Furthermore, the proposed modular design ensures an easier maintenance and update of the system over time. Performance of the proposed system, in terms of perception capabilities, has been evaluated in several underwater contexts taking advantage of the opportunity offered by the MARIS national project. Design issues like energy power consumption, heat dissipation and network capabilities have been evaluated in different scenarios. Finally, real-world experiments, conducted in multiple and variable underwater contexts, including open sea waters, have led to the collection of several datasets that have been publicly released to the scientific community. The vision system has been integrated in a state of the art AUV equipped with a robotic arm and gripper, and has been exploited in the robot control loop to successfully perform underwater grasping operations.