In this article, we describe two techniques to enable haptic-guided teleoperation using 7-DoF cobot arms as master and slave devices. A shortcoming of using cobots as master-slave systems is the lack of force feedback at the master side. However, recent developments in cobot technologies have brought in affordable, flexible, and safe torque-controlled robot arms, which can be programmed to generate force feedback to mimic the operation of a haptic device. In this article, we use two Franka Emika Panda robot arms as a twin master-slave system to enable haptic-guided teleoperation. We propose a two layer mechanism to implement force feedback due to 1) object interactions in the slave workspace, and 2) virtual forces, e.g. those that can repel from static obstacles in the remote environment or provide task-related guidance forces. We present two different approaches for force rendering and conduct an experimental study to evaluate the performance and usability of these approaches in comparison to teleoperation without haptic guidance. Our results indicate that the proposed joint torque coupling method for rendering task forces improves energy requirements during haptic guided telemanipulation, providing realistic force feedback by accurately matching the slave torque readings at the master side.

This paper presents an open-source ROS 2 navigation and sensor platform for quadruped robots, demonstrated on Boston Dynamics Spot in a laboratory environment. The platform integrates SLAM Toolbox for mapping and localisation, Navigation2 with MPPI and Smac Hybrid-A* for global path planning, and a frontier-based autonomous exploration module with practical handling of unreachable frontiers. The paper validates and verifies current, open-source algorithms deployed on off-the-shelf hardware. A greedy wavefront-based frontier selection method is presented that prioritizes Time-to-Closest-Viable-Frontier (TCVF) by terminating the search as soon as a feasible frontier is identified. On a real robot dataset replayed across five goal scenarios, the method reduces median selection latency from $94.31$ ms to $51.08$ ms (95th percentile: $109.54$ ms to $56.99$ ms), corresponding to a $1.85$-times improvement in compute time compared to a standard implementation. The system also employs Zenoh middleware and Foxglove for remote monitoring and control, enabling flexible, high-bandwidth operation. The platform, including configuration files and launch scripts, is released openly to support future research and deployment on quadruped robots.