In this paper, we investigate the use of heightmap-based models to predict deformations in granular materials during teleoperation tasks. Our primary objective is to provide real-time cutting feedback and contact predictions for haptic bilateral teleoperation applications, thereby enhancing operator control in remote manipulation scenarios. We developed a simulation model that utilizes heightmaps to represent deformable materials and implemented a cutting algorithm to simulate complex interactions with granular soils.

Through a series of experiments, we demonstrated that higher resolution heightmaps significantly improve the accuracy and stability of cutting feedback. Our findings suggest that this approach is a viable method for keeping track of changes in a deformable object's shape and can be further expanded to include a wider range of teleoperation tasks, potentially improving the safety and effectiveness of remote operations in hazardous environments.

Being able to do something while not being in the same room could be benefit more people than you know. For this, the improvements made in the world of robotics and network systems world lead to using haptic bilateral teleoperation to being a vi- able option to help with this. However when con- trolling a robot, delays make the experience a lot more difficult and with very precise tasks, like sur- geon trying to make incisions, this could be unac- ceptable when going wrong as there is possibly no way back. A way to mitigate this is by using predic- tive force feedback to aid in this. For this paper, we look into if we can approximate hard physical tran- sitions, like puncturing, to gain satisfactory force feedback for haptic bilateral teleoperation. The basis to getting physical state transition was to model a needle puncturing a piece of paper. For this to be modelled, we have opted to go for a thresh- old mechanism that separates the states from not puncturing to puncturing. To get a first guess on what this threshold should be, physical testing was performed with a real needle and paper. For this actions of applying force with a needle on paper, how been recorded and from it a threshold force has been measured. This results is used for the thresh- old used in the models creation in Bullet physics engine provided by the Networked Systems group. The threshold mechanism, a friction mechanism and mechanism to apply delay on the model simu- lating the delay of the robot have been implemented for this research. This model was then tested for its behaviour over time, which resulted in it performing the way it was expected with respects to what was implemented. Then the model was evaluated in an user study on which different delays have been applied on the model, to gain insight in how immersive the expe- rience is with these delays applied which simulates the reality more when it could be used in combina- tion with a robot arm. The evaluation resulted in it being immersive, while the difficulty of the task of puncturing a piece of paper does increase the more the delay is. With hard physical transitions being able to be approximated with a the model behaving like expected and the force feedback resulting for it being satisfying enough for the user for the model to be immersive enough, makes this hard physical transitions worth continuing researching about in the future.

In this Thesis a fast, low-cost, anthropomorphic robotic hand with tactile feedback is designed. The hand consists of an index finger and a thumb, both of which have four degrees of freedom. All eight degrees of freedom are fully actuated using eight servomotors whose forces are transferred using tendons. The design introduces tendon routing to minimize the change in tendon tension as the joints rotate. To accomplish this at the 2 degree of freedom joints of thumb and index finger, a novel design for the ball and socket joint is created. The hand can be controlled using a tactile glove called the SenseGlove which also enables the user to receive force feedback. Testing reveals that the robot can open and close its fingers within 275 ms, and is able to grab a variety of objects.