Ultrasound imaging is a widely available and highly portable real-time, ionizing radiation-free imaging modality used as first-line in multiple areas. Conventionally, its use is focused on providing 2D imaging using ultrasound probes. However, with the introduction of matrix probes, the acquisition of 3D scans became possible enabling the sonographer to accurately interpret the scanned anatomy without needing to build a possibly error prone 3D mental map and thus, decreasing operator-dependency. Although with this 3D imaging, volume estimation accuracy increases and surveillance becomes less difficult, matrix probes are expensive, have a limited field-of-view and produce a low contrast image. This necessitates the sonographer to still build a mental map whenever a portion of an anatomy is not fully visible in a single volumetric scan, leading to more laborious surveillance. Ultrasound stitching is investigated as a potential method to overcome these limitations by tracking multiple ultrasound scans and merging them using their position and orientation coordinates. To this end, this work uses a robotic arm as the selected tracking system for the stitching of 2D xplane ultrasound images. First, the initial clinical application for the system was derived using a combination of literature study and interviews with medical experts which led to the decision of utilizing the robotic arm for liver imaging and biopsy needle guidance. The suitability of this application was validated with the evaluation of the three required stages namely anatomy reconstruction, needle path planning and needle insertion. Two phantoms mimicking lesions and surrounding vessels were fabricated for this purpose. They were firstly reconstructed by manually segmenting the elements of interest from multiple scans, placing these segmented scans in their respective 3D positions and finally applying an alpha-shapes reconstruction algorithm. Once that the centroid of the lesions was calculated and together with the position information about the surface of the phantom obtained with the robotic arm, it was possible to evaluate all the paths that connect the surface with the centroid and subsequently select only the ones that did not pass next to a vessel within a specific distance. Finally and as an extension of using the robotic arm to track the ultrasound probe, the combined tracking of the probe with a needle holder was investigated for the needle insertion stage. The needle holder was used to maintain the needle always in plane with the ultrasound beam and it was placed at a preset distance with respect to the probe. The holder also provided insertion depth information that facilitated the representation of the needle via a line in the visualization environment whose end indicated the position of the needle tip. This position was updated in real-time with the information received from the needle holder while the needle was being inserted. The position of the needle tip was verified by overlapping real-time ultrasound images with the visualized line. Ultimately, to further illustrate the suitability of the robotic arm in a clinical setting, an ex-vivo and a clinical experiment for vessel tracking and reconstruction was performed.