With the release of various low cost consumer head mounted displays, such as the HTC Vive, virtual reality (VR) visualisation technology is becoming common place. However, haptic interactions continue to lag behind the visual developments. Touch feedback from the HTC Vive system is only provided by way of vibrations in the physical controllers. There are currently no large scale haptic devices that allow a user to experience force feedback in a room scale VR environment. The research presented in this paper demonstrates this problem can be addressed through the use of a large robotic arm to create an encounter haptic solution. Our haptic VR system uses the HTC Vive and the Baxter robot. Positional data is taken from the Vive controllers and sent to one of the Baxter's 7 degrees of freedom arms, which is used to provide force feedback to the user. An experiment was created where a user pushes wooden boxes off a wall in a VR environment. Several tests were performed. Different virtual boxes with a different simulated weight were simulated by varying the speed at which the Baxter moves away from the user. Results from a thirty participant user study indicate that desirable haptic effects can be achieved in a large room scale environment.

This study improves the ergonomics of using the Leap Motion hand tracking device with an Oculus Rift. The improvements were realised through the use of a 3D printed mount that angled the Leap Motion down by 30 degrees. This allowed for users to interact with a virtual environment in which their arms may be held in a biomechanically less stressful location, rather than up and in front of their face. To validate the configuration, 15 participants completed a specially designed task which involved pressing virtual buttons in a given location. The button pressing task was performed in three configurations that compared the angled mount against the standard forward facing mount. Results indicate that the angled mount eliminates tracking loses, whilst producing comparable accuracy against the control condition and allowing the participant to interact in a more natural arm posture.

It is well known that multi-sensory stimulation can enhance immersion within virtual environments. Whilst there has been rapid development of devices which can enhance the visual immersion, technology to stimulate other senses, such as touch, is still under developed. Currently there is a problem wherein a surface in a virtual environment, such as a wall, cannot replicate the physical properties of a solid object. In this paper a novel system is proposed utilising the HTC VIVE and Rethink Robotics' Baxter Robot to replicate surfaces. A demonstration has been created whereby a user climbs a wall in a virtual environment by grabbing onto ledges which exist as a physical body located on Baxter's end effector. The system uses bi-directional TCP communication between an environment developed in Epic Games' Unreal Engine and the Baxter robot running the Robot Operating System framework. When an ascending user reaches out and grabs a ledge on the virtual wall they will be applying a torque to the Baxter arm which can be measured and the intended movement of the user inferred, resulting in the ledge being moved through a suitable Inverse Kinematics path. This has provided the user with the ability to climb a wall in VR in the absence of any hand tracking methods whilst receiving force feedback from the ledges they grasp onto. Current alternative systems only exist as wearables or operate in small spaces. The increased immersion in this VR demo can be used to assist those with phobias of heights.

This article describes experiments that explore the possibility of using an optical tracking device input to remotely control dual-arm robots. We propose using the Leap Motion controller as an alternative to using joysticks, this allows for more intuitive 6-DOF control where only one hand is needed to control each robot arm. We affixed two end effectors to a Baxter research robot, a standard electric gripper, and an AR10 robotic hand. The standard electric gripper was controlled via pinch gestures and all five fingers and thumb were controlled on the AR10 robotic hand using finger movement from the Leap. Some simple tests were performed and the results indicate that in lifting standard objects the standard electric gripper had a higher success rate. The main problem with the hand appeared to be due to the absence of any touch or force feedback to the operator, as the user became more comfortable with the system the better their performance became. This leads us to believe that the use of a robotic hand could be improved with a training program.